As a student, you cannot use Turnitin for free. Turnitin only makes its plagiarism prevention software available to universities and other institutions.
An excellent alternative to Turnitin is Scribbr’s plagiarism checker for students. Scribbr is powered by Turnitin’s plagiarism detection technology and content databases.
If you’re a university representative, you can contact the sales department of Turnitin.
The table of contents in a thesis or dissertation always goes between your abstract and your introduction.
You can use the PEARSON() function to calculate the Pearson correlation coefficient in Excel. If your variables are in columns A and B, then click any blank cell and type “PEARSON(A:A,B:B)”.
There is no function to directly test the significance of the correlation.
You can use the cor() function to calculate the Pearson correlation coefficient in R. To test the significance of the correlation, you can use the cor.test() function.
You should use the Pearson correlation coefficient when (1) the relationship is linear and (2) both variables are quantitative and (3) normally distributed and (4) have no outliers.
The Pearson correlation coefficient (r) is the most common way of measuring a linear correlation. It is a number between –1 and 1 that measures the strength and direction of the relationship between two variables.
This table summarizes the most important differences between normal distributions and Poisson distributions:
| Characteristic | Normal | Poisson |
|---|---|---|
| Continuous or discrete | Continuous | Discrete |
| Parameter | Mean (µ) and standard deviation (σ) | Lambda (λ) |
| Shape | Bell-shaped | Depends on λ |
| Symmetry | Symmetrical | Asymmetrical (right-skewed). As λ increases, the asymmetry decreases. |
| Range | −∞ to ∞ | 0 to ∞ |
When the mean of a Poisson distribution is large (>10), it can be approximated by a normal distribution.
In the Poisson distribution formula, lambda (λ) is the mean number of events within a given interval of time or space. For example, λ = 0.748 floods per year.
The e in the Poisson distribution formula stands for the number 2.718. This number is called Euler’s constant. You can simply substitute e with 2.718 when you’re calculating a Poisson probability. Euler’s constant is a very useful number and is especially important in calculus.
It can sometimes be hard to distinguish accurate from inaccurate sources, especially online. Published articles are not always credible and can reflect a biased viewpoint without providing evidence to support their conclusions.
Information literacy is important because it helps you to be aware of such unreliable content and to evaluate sources effectively, both in an academic context and more generally.
Information literacy refers to a broad range of skills, including the ability to find, evaluate, and use sources of information effectively.
Being information literate means that you:
The three types of skewness are:
Skewness and kurtosis are both important measures of a distribution’s shape.
A parenthetical citation in Chicago author-date style includes the author’s last name, the publication date, and, if applicable, the relevant page number or page range in parentheses. Include a comma after the year, but not after the author’s name.
For example: (Swan 2003, 6)
APA Style distinguishes between parenthetical and narrative citations.
In parenthetical citations, you include all relevant source information in parentheses at the end of the sentence or clause: “Parts of the human body reflect the principles of tensegrity (Levin, 2002).”
In narrative citations, you include the author’s name in the text itself, followed by the publication date in parentheses: “Levin (2002) argues that parts of the human body reflect the principles of tensegrity.”
In a parenthetical citation in MLA style, include the author’s last name and the relevant page number or range in parentheses.
For example: (Eliot 21)
A parenthetical citation gives credit in parentheses to a source that you’re quoting or paraphrasing. It provides relevant information such as the author’s name, the publication date, and the page number(s) cited.
How you use parenthetical citations will depend on your chosen citation style. It will also depend on the type of source you are citing and the number of authors.
APA does not permit the use of ibid. This is because APA in-text citations are parenthetical and there’s no need to shorten them further.
Ibid. may be used in Chicago footnotes or endnotes.
Write “Ibid.” alone when you are citing the same page number and source as the previous citation.
When you are citing the same source, but a different page number, use ibid. followed by a comma and the relevant page number(s). For example:
Only use ibid. if you are directing the reader to a previous full citation of a source.
Ibid. only refers to the previous citation. Therefore, you should only use ibid. directly after a citation that you want to repeat.
A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (“x affects y because …”).
A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses. In a well-designed study, the statistical hypotheses correspond logically to the research hypothesis.
The alternative hypothesis is often abbreviated as Ha or H1. When the alternative hypothesis is written using mathematical symbols, it always includes an inequality symbol (usually ≠, but sometimes < or >).
The null hypothesis is often abbreviated as H0. When the null hypothesis is written using mathematical symbols, it always includes an equality symbol (usually =, but sometimes ≥ or ≤).
You may acknowledge God in your dissertation acknowledgements, but be sure to follow academic convention by also thanking the members of academia, as well as family, colleagues, and friends who helped you.
When searching for sources in databases, think of specific keywords that are relevant to your topic, and consider variations on them or synonyms that might be relevant.
Once you have a clear idea of your research parameters and key terms, choose a database that is relevant to your research (e.g., Medline, JSTOR, Project MUSE).
Find out if the database has a “subject search” option. This can help to refine your search. Use Boolean operators to combine your keywords, exclude specific search terms, and search exact phrases to find the most relevant sources.
Proximity operators are specific words used alongside your chosen keywords that let you specify the proximity of one keyword in relation to another.
The most common proximity operators include NEAR (Nx), WITHIN (Wx), and SENTENCE.
Each proximity operator has a unique function. For example, Nx allows you to find sources that contain the specified keywords within a set number of words (x) of each other.
Boolean operators are specific words and symbols that you can use to expand or narrow your search parameters when using a database or search engine.
The most common Boolean operators are AND, OR, NOT or AND NOT, quotation marks “”, parentheses (), and asterisks *.
Each Boolean operator has a unique function. For example, the Boolean operator AND will provide search results containing both/all of your keywords.
A Boolean search uses specific words and symbols known as Boolean operators (e.g., AND, OR) alongside keywords to limit or expand search results. Boolean searches allow you to:
The t distribution was first described by statistician William Sealy Gosset under the pseudonym “Student.”
To calculate a confidence interval of a mean using the critical value of t, follow these four steps:
To test a hypothesis using the critical value of t, follow these four steps:
You can use the T.INV() function to find the critical value of t for one-tailed tests in Excel, and you can use the T.INV.2T() function for two-tailed tests.
=T.INV.2T(0.05,29)
You can use the qt() function to find the critical value of t in R. The function gives the critical value of t for the one-tailed test. If you want the critical value of t for a two-tailed test, divide the significance level by two.
qt(p = .025, df = 29)
Indirect quotation means reporting what someone said (or wrote) but not using their exact words. It’s similar to paraphrasing, but it only involves changing enough words to fit the statement into your sentence grammatically (e.g., changing the tense or the pronouns).
Since some of the words have changed, indirect quotations are not enclosed in quotation marks.
Quotes within quotes are punctuated differently to distinguish them from the surrounding quote.
Make sure to close both sets of quotes!
The use of single and double quotation marks when quoting differs between US and UK English. In US English, you must use double quotation marks. Single quotation marks are used for quotes within quotes.
In UK English, it’s most common to use single quotation marks, with double quotation marks for quotes within quotes, although the other way around is acceptable too.
Signal phrases can be used in various ways and can be placed at the beginning, middle, or end of a sentence.
To use signal phrases effectively, include:
Different citation styles require you to use specific verb tenses when using signal phrases.
Signal phrases allow you to give credit for an idea or quote to its author or originator. This helps you to:
A signal phrase is a group of words that ascribes a quote or idea to an outside source.
Signal phrases distinguish the cited idea or argument from your own writing and introduce important information including the source of the material that you are quoting, paraphrasing, or summarizing. For example:
“Cognitive psychologist Steven Pinker (1994) insists that humans possess an innate faculty for comprehending grammar.”
You can use the RSQ() function to calculate R² in Excel. If your dependent variable is in column A and your independent variable is in column B, then click any blank cell and type “RSQ(A:A,B:B)”.
You can use the summary() function to view the R² of a linear model in R. You will see the “R-squared” near the bottom of the output.
There are two formulas you can use to calculate the coefficient of determination (R²) of a simple linear regression.
Formula 1: R² = (r)²
Formula 2: R² = 1 − RSS/TSS
The coefficient of determination (R²) is a number between 0 and 1 that measures how well a statistical model predicts an outcome. You can interpret the R² as the proportion of variation in the dependent variable that is predicted by the statistical model.
If you’re quoting from a text that paraphrases or summarizes other sources and cites them in parentheses, APA and Chicago both recommend retaining the citations as part of the quote. However, MLA recommends omitting citations within a quote:
Footnote or endnote numbers that appear within quoted text should be omitted in all styles.
If you want to cite an indirect source (one you’ve only seen quoted in another source), either locate the original source or use the phrase “as cited in” in your citation.
In scientific subjects, the information itself is more important than how it was expressed, so quoting should generally be kept to a minimum. In the arts and humanities, however, well-chosen quotes are often essential to a good paper.
In social sciences, it varies. If your research is mainly quantitative, you won’t include many quotes, but if it’s more qualitative, you may need to quote from the data you collected.
As a general guideline, quotes should take up no more than 5–10% of your paper. If in doubt, check with your instructor or supervisor how much quoting is appropriate in your field.
A literature review is a survey of credible sources on a topic, often used in dissertations, theses, and research papers. Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other academic texts, with an introduction, a main body, and a conclusion.
An annotated bibliography is a list of source references that has a short description (called an annotation) for each of the sources. It is often assigned as part of the research process for a paper.
To present information from other sources in academic writing, it’s best to paraphrase in most cases. This shows that you’ve understood the ideas you’re discussing and incorporates them into your text smoothly.
It’s appropriate to quote when:
To paraphrase effectively, don’t just take the original sentence and swap out some of the words for synonyms. Instead, try:
The main point is to ensure you don’t just copy the structure of the original text, but instead reformulate the idea in your own words.
“Et al.” is an abbreviation of the Latin term “et alia,” which means “and others.” It’s used in source citations to save space when there are too many authors to name them all.
Guidelines for using “et al.” differ depending on the citation style you’re following:
The key difference between observational studies and experimental designs is that a well-done observational study does not influence the responses of participants, while experiments do have some sort of treatment condition applied to at least some participants by random assignment.
An observational study is a great choice for you if your research question is based purely on observations. If there are ethical, logistical, or practical concerns that prevent you from conducting a traditional experiment, an observational study may be a good choice. In an observational study, there is no interference or manipulation of the research subjects, as well as no control or treatment groups.
To insert endnotes in Microsoft Word, follow the steps below:
If you need to change the type of notes used in a Word document from footnotes to endnotes, or the other way around, follow these steps:
To insert a footnote automatically in a Word document:
Footnotes are notes indicated in your text with numbers and placed at the bottom of the page. They’re used to provide:
Be sparing in your use of footnotes (other than citation footnotes), and consider whether the information you’re adding is relevant for the reader.
Footnotes appear at the bottom of the page they refer to. This is convenient for the reader but may cause your text to look cluttered if there are a lot of footnotes.
Endnotes appear all together at the end of the whole text. This may be less convenient for the reader but reduces clutter.
Both footnotes and endnotes are used in the same way: to cite sources or add extra information. You should usually choose one or the other to use in your text, not both.
An in-text citation is an acknowledgement you include in your text whenever you quote or paraphrase a source. It usually gives the author’s last name, the year of publication, and the page number of the relevant text. In-text citations allow the reader to look up the full source information in your reference list and see your sources for themselves.
Academic integrity means being honest, ethical, and thorough in your academic work. To maintain academic integrity, you should avoid misleading your readers about any part of your research and refrain from offenses like plagiarism and contract cheating, which are examples of academic misconduct.
Proofreading rates can be calculated in several different ways. You can set your rate:
A per-word rate is generally the most precise, since it closely reflects the amount of work you’ll have to do. But it can be confusing for clients to parse at a glance; one solution is to quote per 1,000 words so the numbers involved are clearer.
It’s often best to ask a variety of people to review your measurements. You can ask experts, such as other researchers, or laypeople, such as potential participants, to judge the face validity of tests.
While experts have a deep understanding of research methods, the people you’re studying can provide you with valuable insights you may have missed otherwise.
Face validity is important because it’s a simple first step to measuring the overall validity of a test or technique. It’s a relatively intuitive, quick, and easy way to start checking whether a new measure seems useful at first glance.
Good face validity means that anyone who reviews your measure says that it seems to be measuring what it’s supposed to. With poor face validity, someone reviewing your measure may be left confused about what you’re measuring and why you’re using this method.
Face validity is about whether a test appears to measure what it’s supposed to measure. This type of validity is concerned with whether a measure seems relevant and appropriate for what it’s assessing only on the surface.
Statistical analyses are often applied to test validity with data from your measures. You test convergent and discriminant validity with correlations to see if results from your test are positively or negatively related to those of other established tests.
You can also use regression analyses to assess whether your measure is actually predictive of outcomes that you expect it to predict theoretically. A regression analysis that supports your expectations strengthens your claim of construct validity.
When designing or evaluating a measure, construct validity helps you ensure you’re actually measuring the construct you’re interested in. If you don’t have construct validity, you may inadvertently measure unrelated or distinct constructs and lose precision in your research.
Construct validity is often considered the overarching type of measurement validity, because it covers all of the other types. You need to have face validity, content validity, and criterion validity to achieve construct validity.
Construct validity is about how well a test measures the concept it was designed to evaluate. It’s one of four types of measurement validity, which includes construct validity, face validity, and criterion validity.
There are two subtypes of construct validity.
Naturalistic observation is a valuable tool because of its flexibility, external validity, and suitability for topics that can’t be studied in a lab setting.
The downsides of naturalistic observation include its lack of scientific control, ethical considerations, and potential for bias from observers and subjects.
Naturalistic observation is a qualitative research method where you record the behaviors of your research subjects in real world settings. You avoid interfering or influencing anything in a naturalistic observation.
You can think of naturalistic observation as “people watching” with a purpose.
A dependent variable is what changes as a result of the independent variable manipulation in experiments. It’s what you’re interested in measuring, and it “depends” on your independent variable.
In statistics, dependent variables are also called:
An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. It’s called “independent” because it’s not influenced by any other variables in the study.
Independent variables are also called:
As a rule of thumb, questions related to thoughts, beliefs, and feelings work well in focus groups. Take your time formulating strong questions, paying special attention to phrasing. Be careful to avoid leading questions, which can bias your responses.
Overall, your focus group questions should be:
A structured interview is a data collection method that relies on asking questions in a set order to collect data on a topic. They are often quantitative in nature. Structured interviews are best used when:
More flexible interview options include semi-structured interviews, unstructured interviews, and focus groups.
The interviewer effect is a type of bias that emerges when a characteristic of an interviewer (race, age, gender identity, etc.) influences the responses given by the interviewee.
There is a risk of an interviewer effect in all types of interviews, but it can be mitigated by writing really high-quality interview questions.
A semi-structured interview is a blend of structured and unstructured types of interviews. Semi-structured interviews are best used when:
An unstructured interview is the most flexible type of interview, but it is not always the best fit for your research topic.
Unstructured interviews are best used when:
The four most common types of interviews are:
Deductive reasoning is commonly used in scientific research, and it’s especially associated with quantitative research.
In research, you might have come across something called the hypothetico-deductive method. It’s the scientific method of testing hypotheses to check whether your predictions are substantiated by real-world data.
Deductive reasoning is a logical approach where you progress from general ideas to specific conclusions. It’s often contrasted with inductive reasoning, where you start with specific observations and form general conclusions.
Deductive reasoning is also called deductive logic.
Plagiarism is a form of theft, since it involves taking the words and ideas of others and passing them off as your own. As such, it’s academically dishonest and can have serious consequences.
Plagiarism also hinders the learning process, obscuring the sources of your ideas and usually resulting in bad writing. Even if you could get away with it, plagiarism harms your own learning.
There are many different types of inductive reasoning that people use formally or informally.
Here are a few common types:
Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down.
Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions.
In inductive research, you start by making observations or gathering data. Then, you take a broad scan of your data and search for patterns. Finally, you make general conclusions that you might incorporate into theories.
Inductive reasoning is a method of drawing conclusions by going from the specific to the general. It’s usually contrasted with deductive reasoning, where you proceed from general information to specific conclusions.
Inductive reasoning is also called inductive logic or bottom-up reasoning.
A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.
A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).
Triangulation can help:
But triangulation can also pose problems:
There are four main types of triangulation:
Yes, APA language guidelines state that you should always use the serial comma (aka Oxford comma) in your writing.
This means including a comma before the word “and” at the end of a list of three or more items: “spelling, grammar, and punctuation.” Doing this consistently tends to make your lists less ambiguous.
Yes, it’s perfectly valid to write sentences in the passive voice. The APA language guidelines do caution against overusing the passive voice, because it can obscure your meaning or be needlessly long-winded. For this reason, default to the active voice in most cases.
The passive voice is most useful when the point of the sentence is just to state what was done, not to emphasize who did it. For example, “The projector was mounted on the wall” is better than “James and I mounted the projector on the wall” if it’s not particularly important who mounted the projector.
Yes, APA language guidelines encourage you to use the first-person pronouns “I” or “we” when referring to yourself or a group including yourself in your writing.
In APA Style, you should not refer to yourself in the third person. For example, do not refer to yourself as “the researcher” or “the author” but simply as “I” or “me.” Referring to yourself in the third person is an older academic convention that is mostly considered confusing and unnecessary today.
Many academic fields use peer review, largely to determine whether a manuscript is suitable for publication. Peer review enhances the credibility of the published manuscript.
However, peer review is also common in non-academic settings. The United Nations, the European Union, and many individual nations use peer review to evaluate grant applications. It is also widely used in medical and health-related fields as a teaching or quality-of-care measure.
Peer assessment is often used in the classroom as a pedagogical tool. Both receiving feedback and providing it are thought to enhance the learning process, helping students think critically and collaboratively.
Peer review can stop obviously problematic, falsified, or otherwise untrustworthy research from being published. It also represents an excellent opportunity to get feedback from renowned experts in your field. It acts as a first defense, helping you ensure your argument is clear and that there are no gaps, vague terms, or unanswered questions for readers who weren’t involved in the research process.
Peer-reviewed articles are considered a highly credible source due to this stringent process they go through before publication.
In general, the peer review process follows the following steps:
Most online plagiarism checkers only have access to public databases, whose software doesn’t allow you to compare two documents for plagiarism.
However, in addition to our Plagiarism Checker, Scribbr also offers an Self-Plagiarism Checker. This is an add-on tool that lets you compare your paper with unpublished or private documents. This way you can rest assured that you haven’t unintentionally plagiarized or self-plagiarized.
Compare two sources for plagiarism
The observer-expectancy effect occurs when researchers influence the results of their own study through interactions with participants.
Researchers’ own beliefs and expectations about the study results may unintentionally influence participants through demand characteristics.
You can use several tactics to minimize observer bias.
It’s impossible to completely avoid observer bias in studies where data collection is done or recorded manually, but you can take steps to reduce observer bias in your research.
Observer bias occurs when a researcher’s expectations, opinions, or prejudices influence what they perceive or record in a study. It usually affects studies when observers are aware of the research aims or hypotheses. Observer bias is also called detection bias or ascertainment bias.
There are three main types of missing data.
Missing completely at random (MCAR) data are randomly distributed across the variable and unrelated to other variables.
Missing at random (MAR) data are not randomly distributed but they are accounted for by other observed variables.
Missing not at random (MNAR) data systematically differ from the observed values.
To tidy up your missing data, your options usually include accepting, removing, or recreating the missing data.
Missing data are important because, depending on the type, they can sometimes bias your results. This means your results may not be generalizable outside of your study because your data come from an unrepresentative sample.
Missing data, or missing values, occur when you don’t have data stored for certain variables or participants.
In any dataset, there’s usually some missing data. In quantitative research, missing values appear as blank cells in your spreadsheet.
Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.
You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.
Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. It is often used when the issue you’re studying is new, or the data collection process is challenging in some way.
Explanatory research is used to investigate how or why a phenomenon occurs. Therefore, this type of research is often one of the first stages in the research process, serving as a jumping-off point for future research.
Exploratory research aims to explore the main aspects of an under-researched problem, while explanatory research aims to explain the causes and consequences of a well-defined problem.
Explanatory research is a research method used to investigate how or why something occurs when only a small amount of information is available pertaining to that topic. It can help you increase your understanding of a given topic.
There are two steps to calculating the geometric mean:
Before calculating the geometric mean, note that:
The arithmetic mean is the most commonly used type of mean and is often referred to simply as “the mean.” While the arithmetic mean is based on adding and dividing values, the geometric mean multiplies and finds the root of values.
Even though the geometric mean is a less common measure of central tendency, it’s more accurate than the arithmetic mean for percentage change and positively skewed data. The geometric mean is often reported for financial indices and population growth rates.
The geometric mean is an average that multiplies all values and finds a root of the number. For a dataset with n numbers, you find the nth root of their product.
Outliers are extreme values that differ from most values in the dataset. You find outliers at the extreme ends of your dataset.
It’s best to remove outliers only when you have a sound reason for doing so.
Some outliers represent natural variations in the population, and they should be left as is in your dataset. These are called true outliers.
Other outliers are problematic and should be removed because they represent measurement errors, data entry or processing errors, or poor sampling.
You can choose from four main ways to detect outliers:
Outliers can have a big impact on your statistical analyses and skew the results of any hypothesis test if they are inaccurate.
These extreme values can impact your statistical power as well, making it hard to detect a true effect if there is one.
Clean data are valid, accurate, complete, consistent, unique, and uniform. Dirty data include inconsistencies and errors.
Dirty data can come from any part of the research process, including poor research design, inappropriate measurement materials, or flawed data entry.
Data cleaning takes place between data collection and data analyses. But you can use some methods even before collecting data.
For clean data, you should start by designing measures that collect valid data. Data validation at the time of data entry or collection helps you minimize the amount of data cleaning you’ll need to do.
After data collection, you can use data standardization and data transformation to clean your data. You’ll also deal with any missing values, outliers, and duplicate values.
Every dataset requires different techniques to clean dirty data, but you need to address these issues in a systematic way. You focus on finding and resolving data points that don’t agree or fit with the rest of your dataset.
These data might be missing values, outliers, duplicate values, incorrectly formatted, or irrelevant. You’ll start with screening and diagnosing your data. Then, you’ll often standardize and accept or remove data to make your dataset consistent and valid.
Data cleaning is necessary for valid and appropriate analyses. Dirty data contain inconsistencies or errors, but cleaning your data helps you minimize or resolve these.
Without data cleaning, you could end up with a Type I or II error in your conclusion. These types of erroneous conclusions can be practically significant with important consequences, because they lead to misplaced investments or missed opportunities.
Data cleaning involves spotting and resolving potential data inconsistencies or errors to improve your data quality. An error is any value (e.g., recorded weight) that doesn’t reflect the true value (e.g., actual weight) of something that’s being measured.
In this process, you review, analyze, detect, modify, or remove “dirty” data to make your dataset “clean.” Data cleaning is also called data cleansing or data scrubbing.
When writing your Common App essay, choose a prompt that sparks your interest and that you can connect to a unique personal story.
No matter which prompt you choose, admissions officers are more interested in your ability to demonstrate personal development, insight, or motivation for a certain area of study.
The Common App essay is your primary writing sample within the Common Application, a college application portal accepted by more than 900 schools. All your prospective schools that accept the Common App will read this essay to understand your character, background, and value as a potential student.
Since this essay is read by many colleges, avoid mentioning any college names or programs; instead, save tailored answers for the supplementary school-specific essays within the Common App.
Most importantly, your essay should be about you, not another person or thing. An insightful college admissions essay requires deep self-reflection, authenticity, and a balance between confidence and vulnerability.
Your essay shouldn’t be a résumé of your experiences but instead should tell a story that demonstrates your most important values and qualities.
Most institutions have an internal database of previously submitted student papers. Turnitin can check for self-plagiarism by comparing your paper against this database. If you’ve reused parts of an assignment you already submitted, it will flag any similarities as potential plagiarism.
Online plagiarism checkers don’t have access to your institution’s database, so they can’t detect self-plagiarism of unpublished work. If you’re worried about accidentally self-plagiarizing, you can use Scribbr’s Self-Plagiarism Checker to upload your unpublished documents and check them for similarities.
When revising your college essay, first check for big-picture issues regarding your message and content. Then, check for flow, tone, style, and clarity. Finally, focus on eliminating grammar and punctuation errors.
If your college essay goes over the word count limit, cut any sentences with tangents or irrelevant details. Delete unnecessary words that clutter your essay.
If you’re struggling to reach the word count for your college essay, add vivid personal stories or share your feelings and insight to give your essay more depth and authenticity.
If you’ve got to write your college essay fast, don’t panic. First, set yourself deadlines: you should spend about 10% of your remaining time on brainstorming, 10% on outlining, 40% writing, 30% revising, and 10% taking breaks in between stages.
Second, brainstorm stories and values based on your essay prompt.
Third, outline your essay based on the montage or narrative essay structure.
Fourth, write specific, personal, and unique stories that would be hard for other students to replicate.
Fifth, revise your essay and make sure it’s clearly written.
Last, if possible, get feedback from an essay coach. Scribbr essay editors can help you revise your essay in 12 hours or less.
If you have a small amount of attrition bias, you can use some statistical methods to try to make up for it.
Multiple imputation involves using simulations to replace the missing data with likely values. Alternatively, you can use sample weighting to make up for the uneven balance of participants in your sample.
To avoid attrition, applying some of these measures can help you reduce participant dropout by making it easy and appealing for participants to stay.
Attrition bias can skew your sample so that your final sample differs significantly from your original sample. Your sample is biased because some groups from your population are underrepresented.
With a biased final sample, you may not be able to generalize your findings to the original population that you sampled from, so your external validity is compromised.
Attrition bias is a threat to internal validity. In experiments, differential rates of attrition between treatment and control groups can skew results.
This bias can affect the relationship between your independent and dependent variables. It can make variables appear to be correlated when they are not, or vice versa.
Some attrition is normal and to be expected in research. However, the type of attrition is important because systematic bias can distort your findings. Attrition bias can lead to inaccurate results because it affects internal and/or external validity.
Attrition bias is the selective dropout of some participants who systematically differ from those who remain in the study.
Some groups of participants may leave because of bad experiences, unwanted side effects, or inadequate incentives for participation, among other reasons. Attrition is also called subject mortality, but it doesn’t always refer to participants dying!
Avoid swearing in a college essay, since admissions officers’ opinions of profanity will vary. In some cases, it might be okay to use a vulgar word, such as in dialogue or quotes that make an important point in your essay. However, it’s safest to try to make the same point without swearing.
If you have bad grades on your transcript, you may want to use your college admissions essay to explain the challenging circumstances that led to them. Make sure to avoid dwelling on the negative aspects and highlight how you overcame the situation or learned an important lesson.
However, some college applications offer an additional information section where you can explain your bad grades, allowing you to choose another meaningful topic for your college essay.
Here’s a brief list of college essay topics that may be considered cliché:
It’s easier to write a standout essay with a unique topic. However, it’s possible to make a common topic compelling with interesting story arcs, uncommon connections, and an advanced writing style.
Yes. The college application essay is less formal than other academic writing—though of course it’s not mandatory to use contractions in your essay.
In a college essay, you can be creative with your language. When writing about the past, you can use the present tense to make the reader feel as if they were there in the moment with you. But make sure to maintain consistency and when in doubt, default to the correct verb tense according to the time you’re writing about.
The college admissions essay gives admissions officers a different perspective on you beyond your academic achievements, test scores, and extracurriculars. It’s your chance to stand out from other applicants with similar academic profiles by telling a unique, personal, and specific story.
Use a standard font such as Times New Roman or Arial to avoid distracting the reader from your college essay’s content.
A college application essay is less formal than most academic writing. Instead of citing sources formally with in-text citations and a reference list, you can cite them informally in your text.
For example, “In her research paper on genetics, Quinn Roberts explores …”
There is no set number of paragraphs in a college admissions essay. College admissions essays can diverge from the traditional five-paragraph essay structure that you learned in English class. Just make sure to stay under the specified word count.
Most topics are acceptable for college essays if you can use them to demonstrate personal growth or a lesson learned. However, there are a few difficult topics for college essays that should be avoided. Avoid topics that are:
To write an effective diversity essay, include vulnerable, authentic stories about your unique identity, background, or perspective. Provide insight into how your lived experience has influenced your outlook, activities, and goals. If relevant, you should also mention how your background has led you to apply for this university and why you’re a good fit.
Many universities believe a student body composed of different perspectives, beliefs, identities, and backgrounds will enhance the campus learning and community experience.
Admissions officers are interested in hearing about how your unique background, identity, beliefs, culture, or characteristics will enrich the campus community, which is why they assign a diversity essay.
In addition to your main college essay, some schools and scholarships may ask for a supplementary essay focused on an aspect of your identity or background. This is sometimes called a diversity essay.
You can use humor in a college essay, but carefully consider its purpose and use it wisely. An effective use of humor involves unexpected, keen observations of the everyday, or speaks to a deeper theme. Humor shouldn’t be the main focus of the essay, but rather a tool to improve your storytelling.
Get a second opinion from a teacher, counselor, or essay coach on whether your essay’s humor is appropriate.
Though admissions officers are interested in hearing your story, they’re also interested in how you tell it. An exceptionally written essay will differentiate you from other applicants, meaning that admissions officers will spend more time reading it.
You can use literary devices to catch your reader’s attention and enrich your storytelling; however, focus on using just a few devices well, rather than trying to use as many as possible.
To decide on a good college essay topic, spend time thoughtfully answering brainstorming questions. If you still have trouble identifying topics, try the following two strategies:
You can also ask family, friends, or mentors to help you brainstorm topics, give feedback on your potential essay topics, or recall key stories that showcase your qualities.
Yes—admissions officers don’t expect everyone to have a totally unique college essay topic. But you must differentiate your essay from others by having a surprising story arc, an interesting insight, and/or an advanced writing style.
There are no foolproof college essay topics—whatever your topic, the key is to write about it effectively. However, a good topic
You can control demand characteristics by taking a few precautions in your research design and materials.
Use these measures:
Demand characteristics are a type of extraneous variable that can affect the outcomes of the study. They can invalidate studies by providing an alternative explanation for the results.
These cues may nudge participants to consciously or unconsciously change their responses, and they pose a threat to both internal and external validity. You can’t be sure that your independent variable manipulation worked, or that your findings can be applied to other people or settings.
In research, demand characteristics are cues that might indicate the aim of a study to participants. These cues can lead to participants changing their behaviors or responses based on what they think the research is about.
Demand characteristics are common problems in psychology experiments and other social science studies because they can bias your research findings.
Unlike a five-paragraph essay, your admissions essay should not end by summarizing the points you’ve already made. It’s better to be creative and aim for a strong final impression.
You should also avoid stating the obvious (for example, saying that you hope to be accepted).
There are a few strategies you can use for a memorable ending to your college essay:
The best technique will depend on your topic choice, essay outline, and writing style. You can write several endings using different techniques to see which works best.
Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. It’s a form of academic fraud.
These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement but a serious ethical failure.
Anonymity means you don’t know who the participants are, while confidentiality means you know who they are but remove identifying information from your research report. Both are important ethical considerations.
You can only guarantee anonymity by not collecting any personally identifying information—for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos.
You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals.
Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe.
Ethical considerations in research are a set of principles that guide your research designs and practices. These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication.
Scientists and researchers must always adhere to a certain code of conduct when collecting data from others.
These considerations protect the rights of research participants, enhance research validity, and maintain scientific integrity.
College deadlines vary depending on the schools you’re applying to and your application plan:
Depending on your prospective schools’ requirements, you may need to submit scores for the SAT or ACT as part of your college application.
Some schools now no longer require students to submit test scores; however, you should still take the SAT or ACT and aim to get a high score to strengthen your application package.
Aim to take the SAT or ACT in the spring of your junior year to give yourself enough time to retake it in the fall of your senior year if necessary.
Apply early for federal student aid and application fee waivers. You can also look for scholarships from schools, corporations, and charitable foundations.
To maximize your options, you should aim to apply to about eight schools:
The college admissions essay accounts for roughly 25% of the weight of your application.
At highly selective schools, there are four qualified candidates for every spot. While your academic achievements are important, your college admissions essay can help you stand out from other applicants with similar profiles.
In general, for your college application you will need to submit all of the following:
Different colleges may have specific requirements, so make sure you check exactly what’s expected in the application guidance.
You should start thinking about your college applications the summer before your junior year to give you sufficient time for college visits, taking standardized tests, applying for financial aid, writing essays, and collecting application material.
Yes, but make sure your essay directly addresses the prompt, respects the word count, and demonstrates the organization’s values.
If you plan ahead, you can save time by writing one scholarship essay for multiple prompts with similar questions. In a scholarship tracker spreadsheet, you can group or color-code overlapping essay prompts; then, write a single essay for multiple scholarships. Sometimes, you can even reuse or adapt your main college essay.
You can start applying for scholarships as early as your junior year. Continue applying throughout your senior year.
Invest time in applying for various scholarships, especially local ones with small dollar amounts, which are likely easier to win and more reflective of your background and interests. It will be easier for you to write an authentic and compelling essay if the scholarship topic is meaningful to you.
You can find scholarships through your school counselor, community network, or an internet search.
A scholarship essay requires you to demonstrate your values and qualities while answering the prompt’s specific question.
After researching the scholarship organization, identify a personal experience that embodies its values and exemplifies how you will be a successful student.
A standout college essay has several key ingredients:
While timelines will differ depending on the student, plan on spending at least 1–3 weeks brainstorming and writing the first draft of your college admissions essay, and at least 2–4 weeks revising across multiple drafts. Don’t forget to save enough time for breaks between each writing and editing stage.
You should already begin thinking about your essay the summer before your senior year so that you have plenty of time to try out different topics and get feedback on what works.
Your college essay accounts for about 25% of your application’s weight. It may be the deciding factor in whether you’re accepted, especially for competitive schools where most applicants have exceptional grades, test scores, and extracurricular track records.
In most cases, quoting other people isn’t a good way to start your college essay. Admissions officers want to hear your thoughts about yourself, and quotes often don’t achieve that. Unless a quote truly adds something important to your essay that it otherwise wouldn’t have, you probably shouldn’t include it.
Cliché openers in a college essay introduction are usually general and applicable to many students and situations. Most successful introductions are specific: they only work for the unique essay that follows.
The key to a strong college essay introduction is not to give too much away. Try to start with a surprising statement or image that raises questions and compels the reader to find out more.
The introduction of your college essay is the first thing admissions officers will read and therefore your most important opportunity to stand out. An excellent introduction will keep admissions officers reading, allowing you to tell them what you want them to know.
Yes, reusing your own work without acknowledgment is considered self-plagiarism. This can range from re-submitting an entire assignment to reusing passages or data from something you’ve turned in previously without citing them.
Self-plagiarism often has the same consequences as other types of plagiarism. If you want to reuse content you wrote in the past, make sure to check your university’s policy or consult your professor.
If you are reusing content or data you used in a previous assignment, make sure to cite yourself. You can cite yourself just as you would cite any other source: simply follow the directions for that source type in the citation style you are using.
Keep in mind that reusing your previous work can be considered self-plagiarism, so make sure you ask your professor or consult your university’s handbook before doing so.
If your college essay goes over the word count limit, cut any sentences with tangents or irrelevant details. Delete unnecessary words that clutter your essay.
If you’re struggling to reach the word count for your college essay, add vivid personal stories or share your feelings and insight to give your essay more depth and authenticity.
Most college application portals specify a word count range for your essay, and you should stay within 10% of the upper limit to write a developed and thoughtful essay.
You should aim to stay under the specified word count limit to show you can follow directions and write concisely. However, don’t write too little, as it may seem like you are unwilling or unable to write a detailed and insightful narrative about yourself.
If no word count is specified, we advise keeping your essay between 400 and 600 words.
In your application essay, admissions officers are looking for particular features: they want to see context on your background, positive traits that you could bring to campus, and examples of you demonstrating those qualities.
Colleges want to be able to differentiate students who seem similar on paper. In the college application essay, they’re looking for a way to understand each applicant’s unique personality and experiences.
You don’t need a title for your college admissions essay, but you can include one if you think it adds something important.
Your college essay’s format should be as simple as possible:
There are no set rules for how to structure a college application essay, but these are two common structures that work:
Avoid the five-paragraph essay structure that you learned in high school.
Campus visits are always helpful, but if you can’t make it in person, the college website will have plenty of information for you to explore. You should look through the course catalog and even reach out to current faculty with any questions about the school.
Colleges set a “Why this college?” essay because they want to see that you’ve done your research. You must prove that you know what makes the school unique and can connect that to your own personal goals and academic interests.
Depending on your writing, you may go through several rounds of revision. Make sure to put aside your essay for a little while after each editing stage to return with a fresh perspective.
Teachers and guidance counselors can help you check your language, tone, and content. Ask for their help at least one to two months before the submission deadline, as many other students will also want their help.
Friends and family are a good resource to check for authenticity. It’s best to seek help from family members with a strong writing or English educational background, or from older siblings and cousins who have been through the college admissions process.
If possible, get help from an essay coach or editor; they’ll have specialized knowledge of college admissions essays and be able to give objective expert feedback.
When revising your college essay, first check for big-picture issues regarding message, flow, tone, style, and clarity. Then, focus on eliminating grammar and punctuation errors.
Include specific, personal details and use your authentic voice to shed a new perspective on a common human experience.
Through specific stories, you can weave your achievements and qualities into your essay so that it doesn’t seem like you’re bragging from a resume.
When writing about yourself, including difficult experiences or failures can be a great way to show vulnerability and authenticity, but be careful not to overshare, and focus on showing how you matured from the experience.
First, spend time reflecting on your core values and character. You can start with these questions:
However, you should do a comprehensive brainstorming session to fully understand your values. Also consider how your values and goals match your prospective university’s program and culture. Then, brainstorm stories that illustrate the fit between the two.
In a college application essay, you can occasionally bend grammatical rules if doing so adds value to the storytelling process and the essay maintains clarity.
However, use standard language rules if your stylistic choices would otherwise distract the reader from your overall narrative or could be easily interpreted as unintentional errors.
Write concisely and use the active voice to maintain a quick pace throughout your essay and make sure it’s the right length. Avoid adding definitions unless they provide necessary explanation.
Use first-person “I” statements to speak from your perspective. Use appropriate word choices that show off your vocabulary but don’t sound like you used a thesaurus. Avoid using idioms or cliché expressions by rewriting them in a creative, original way.
If you’re an international student applying to a US college and you’re comfortable using American idioms or cultural references, you can. But instead of potentially using them incorrectly, don’t be afraid to write in detail about yourself within your own culture.
Provide context for any words, customs, or places that an American admissions officer might be unfamiliar with.
College application essays are less formal than other kinds of academic writing. Use a conversational yet respectful tone, as if speaking with a teacher or mentor. Be vulnerable about your feelings, thoughts, and experiences to connect with the reader.
Aim to write in your authentic voice, with a style that sounds natural and genuine. You can be creative with your word choice, but don’t use elaborate vocabulary to impress admissions officers.
Admissions officers use college admissions essays to evaluate your character, writing skills, and ability to self-reflect. The essay is your chance to show what you will add to the academic community.
The college essay may be the deciding factor in your application, especially for competitive schools where most applicants have exceptional grades, test scores, and extracurriculars.
Some colleges also require supplemental essays about specific topics, such as why you chose that specific college. Scholarship essays are often required to obtain financial aid.
Common knowledge does not need to be cited. However, you should be extra careful when deciding what counts as common knowledge.
Common knowledge encompasses information that the average educated reader would accept as true without needing the extra validation of a source or citation.
Common knowledge should be widely known, undisputed and easily verified. When in doubt, always cite your sources.
Plagiarism has serious consequences, and can indeed be illegal in certain scenarios.
While most of the time plagiarism in an undergraduate setting is not illegal, plagiarism or self-plagiarism in a professional academic setting can lead to legal action, including copyright infringement and fraud. Many scholarly journals do not allow you to submit the same work to more than one journal, and if you do not credit a co-author, you could be legally defrauding them.
Even if you aren’t breaking the law, plagiarism can seriously impact your academic career. While the exact consequences of plagiarism vary by institution and severity, common consequences include: a lower grade, automatically failing a course, academic suspension or probation, or even expulsion.
Accidental plagiarism is one of the most common examples of plagiarism. Perhaps you forgot to cite a source, or paraphrased something a bit too closely. Maybe you can’t remember where you got an idea from, and aren’t totally sure if it’s original or not.
These all count as plagiarism, even though you didn’t do it on purpose. When in doubt, make sure you’re citing your sources. Also consider running your work through a plagiarism checker tool prior to submission, which work by using advanced database software to scan for matches between your text and existing texts.
Scribbr’s Plagiarism Checker takes less than 10 minutes and can help you turn in your paper with confidence.
Self-plagiarism means recycling work that you’ve previously published or submitted as an assignment. It’s considered academic dishonesty to present something as brand new when you’ve already gotten credit and perhaps feedback for it in the past.
If you want to refer to ideas or data from previous work, be sure to cite yourself.
If you’re concerned that you may have self-plagiarized, Scribbr’s Self-Plagiarism Checker can help you turn in your paper with confidence. It compares your work to unpublished or private documents that you upload, so you can rest assured that you haven’t unintentionally plagiarized.
Incremental plagiarism means inserting quotes, passages, or excerpts from other works into your assignment without properly citing the original source.
Even if the vast majority of the text is yours, including any content that isn’t without citing it is plagiarism.
Consider using a plagiarism checker yourself before submitting your work. Plagiarism checkers work by scanning your document, comparing it to a database of webpages and publications, and highlighting passages that appear similar to other texts.
Scribbr’s Plagiarism Checker takes less than 10 minutes and can help you turn in your paper with confidence.
Patchwork plagiarism (aka mosaic plagiarism) means copying phrases, passages, or ideas from various existing sources and combining them to create a new text. While this type of plagiarism is more insidious than simply copy-pasting directly from a source, plagiarism checkers like Turnitin’s can still easily detect it.
To avoid plagiarism in any form, remember to cite your sources. Also consider running your work through a plagiarism checker tool prior to submission, which work by using advanced database software to scan for matches between your text and existing texts.
Scribbr’s Plagiarism Checker takes less than 10 minutes and can help you turn in your paper with confidence.
Verbatim plagiarism means copying text from a source and pasting it directly into your own document without giving proper credit.
Even if you delete a few words or replace them with synonyms, it still counts as verbatim plagiarism.
To use an author’s exact words, quote the original source by putting the copied text in quotation marks and including an in-text citation.
If you’re worried abotu plagiarism, consider running your work through a plagiarism checker tool prior to submission, which work by using advanced database software to scan for matches between your text and existing texts.
Scribbr’s Plagiarism Checker takes less than 10 minutes and can help you turn in your paper with confidence.
Global plagiarism means taking an entire work written by someone else and passing it off as your own. This can mean getting someone else to write an essay or assignment for you, or submitting a text you found online as your own work.
Global plagiarism is the most serious type of plagiarism because it involves deliberately and directly lying about the authorship of a work. It can have severe consequences.
To ensure you aren’t accidentally plagiarizing, consider running your work through plagiarism checker tool prior to submission. These tools work by using advanced database software to scan for matches between your text and existing texts.
Scribbr’s Plagiarism Checker takes less than 10 minutes and can help you turn in your paper with confidence.
Plagiarism can be detected by your professor or readers if the tone, formatting, or style of your text is different in different parts of your paper, or if they’re familiar with the plagiarized source.
Many universities also use plagiarism detection software like Turnitin’s, which compares your text to a large database of other sources, flagging any similarities that come up.
It can be easier than you think to commit plagiarism by accident. Consider using a plagiarism checker prior to submitting your paper to ensure you haven’t missed any citations.
Some examples of plagiarism include:
The most surefire way to avoid plagiarism is to always cite your sources. When in doubt, cite!
If you’re concerned about plagiarism, consider running your work through a plagiarism checker tool prior to submission. Scribbr’s Plagiarism Checker takes less than 10 minutes and can help you turn in your paper with confidence.
Plagiarism means presenting someone else’s work as your own without giving proper credit to the original author. In academic writing, plagiarism involves using words, ideas, or information from a source without including a citation.
Plagiarism can have serious consequences, even when it’s done accidentally. To avoid plagiarism, it’s important to keep track of your sources and cite them correctly.
A credible source should pass the CRAAP test and follow these guidelines:
The CRAAP test is an acronym to help you evaluate the credibility of a source you are considering using. It is an important component of information literacy.
The CRAAP test has five main components:
Peer review is a process of evaluating submissions to an academic journal. Utilizing rigorous criteria, a panel of reviewers in the same subject area decide whether to accept each submission for publication. For this reason, academic journals are often considered among the most credible sources you can use in a research project– provided that the journal itself is trustworthy and well-regarded.
Academic dishonesty can be intentional or unintentional, ranging from something as simple as claiming to have read something you didn’t to copying your neighbor’s answers on an exam.
You can commit academic dishonesty with the best of intentions, such as helping a friend cheat on a paper. Severe academic dishonesty can include buying a pre-written essay or the answers to a multiple-choice test, or falsifying a medical emergency to avoid taking a final exam.
Consequences of academic dishonesty depend on the severity of the offense and your institution’s policy. They can range from a warning for a first offense to a failing grade in a course to expulsion from your university.
For those in certain fields, such as nursing, engineering, or lab sciences, not learning fundamentals properly can directly impact the health and safety of others. For those working in academia or research, academic dishonesty impacts your professional reputation, leading others to doubt your future work.
Academic dishonesty refers to deceitful or misleading behavior in an academic setting. Academic dishonesty can occur intentionally or unintentionally, and varies in severity.
It can encompass paying for a pre-written essay, cheating on an exam, or committing plagiarism. It can also include helping others cheat, copying a friend’s homework answers, or even pretending to be sick to miss an exam.
Academic dishonesty doesn’t just occur in a classroom setting, but also in research and other academic-adjacent fields.
In multistage sampling, you can use probability or non-probability sampling methods.
For a probability sample, you have to probability sampling at every stage. You can mix it up by using simple random sampling, systematic sampling, or stratified sampling to select units at different stages, depending on what is applicable and relevant to your study.
Multistage sampling can simplify data collection when you have large, geographically spread samples, and you can obtain a probability sample without a complete sampling frame.
But multistage sampling may not lead to a representative sample, and larger samples are needed for multistage samples to achieve the statistical properties of simple random samples.
These are four of the most common mixed methods designs:
Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question. It’s a research strategy that can help you enhance the validity and credibility of your findings.
Triangulation is mainly used in qualitative research, but it’s also commonly applied in quantitative research. Mixed methods research always uses triangulation.
In multistage sampling, or multistage cluster sampling, you draw a sample from a population using smaller and smaller groups at each stage.
This method is often used to collect data from a large, geographically spread group of people in national surveys, for example. You take advantage of hierarchical groupings (e.g., from state to city to neighborhood) to create a sample that’s less expensive and time-consuming to collect data from.
No, the steepness or slope of the line isn’t related to the correlation coefficient value. The correlation coefficient only tells you how closely your data fit on a line, so two datasets with the same correlation coefficient can have very different slopes.
To find the slope of the line, you’ll need to perform a regression analysis.
Correlation coefficients always range between -1 and 1.
The sign of the coefficient tells you the direction of the relationship: a positive value means the variables change together in the same direction, while a negative value means they change together in opposite directions.
The absolute value of a number is equal to the number without its sign. The absolute value of a correlation coefficient tells you the magnitude of the correlation: the greater the absolute value, the stronger the correlation.
These are the assumptions your data must meet if you want to use Pearson’s r:
In MLA style, footnotes or endnotes can be used to provide additional information that would interrupt the flow of your text.
This can be further examples or developments of ideas you only briefly discuss in the text. You can also use notes to provide additional sources or explain your citation practice.
You don’t have to use any notes at all; only use them to provide relevant information that complements your arguments or helps the reader to understand them.
No, the MLA standard is to use parenthetical in-text citations to cite sources. Footnotes or endnotes can be used to add extra information that doesn’t fit into your main text, but they’re not needed for citations.
If you need to cite a lot of sources at the same point in the text, though, placing these citations in a note can be a good way to avoid cluttering your text.
Quantitative research designs can be divided into two main categories:
Qualitative research designs tend to be more flexible. Common types of qualitative design include case study, ethnography, and grounded theory designs.
A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources. This allows you to draw valid, trustworthy conclusions.
The priorities of a research design can vary depending on the field, but you usually have to specify:
A research design is a strategy for answering your research question. It defines your overall approach and determines how you will collect and analyze data.
To apply a hanging indent to your reference list or Works Cited list in Word or Google Docs, follow the steps below.
Microsoft Word:
Google Docs:
When the hanging indent is applied, for each reference, every line except the first is indented. This helps the reader see where one entry ends and the next begins.
According to MLA format guidelines, the Works Cited page(s) should look like this:
The MLA Works Cited lists every source that you cited in your paper. Each entry contains the author, title, and publication details of the source.
Questionnaires can be self-administered or researcher-administered.
Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or through mail. All questions are standardized so that all respondents receive the same questions with identical wording.
Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.
You can organize the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomization can minimize the bias from order effects.
Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.
Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.
A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires.
No, MLA states that in an annotated bibliography, you can write short phrases instead of full sentences to keep your annotations concise. You can still choose to use full sentences instead, though.
Use full sentences in your annotations if your instructor requires you to, and always use full sentences in the main text of your paper.
Usually, no title page is needed in an MLA paper. A header is generally included at the top of the first page instead. The exceptions are when
In those cases, you should use a title page instead of a header, listing the same information but on a separate page.
The third variable and directionality problems are two main reasons why correlation isn’t causation.
The third variable problem means that a confounding variable affects both variables to make them seem causally related when they are not.
The directionality problem is when two variables correlate and might actually have a causal relationship, but it’s impossible to conclude which variable causes changes in the other.
Correlation describes an association between variables: when one variable changes, so does the other. A correlation is a statistical indicator of the relationship between variables.
Causation means that changes in one variable brings about changes in the other; there is a cause-and-effect relationship between variables. The two variables are correlated with each other, and there’s also a causal link between them.
Controlled experiments establish causality, whereas correlational studies only show associations between variables.
In general, correlational research is high in external validity while experimental research is high in internal validity.
A correlation is usually tested for two variables at a time, but you can test correlations between three or more variables.
A correlation coefficient is a single number that describes the strength and direction of the relationship between your variables.
Different types of correlation coefficients might be appropriate for your data based on their levels of measurement and distributions. The Pearson product-moment correlation coefficient (Pearson’s r) is commonly used to assess a linear relationship between two quantitative variables.
A correlational research design investigates relationships between two variables (or more) without the researcher controlling or manipulating any of them. It’s a non-experimental type of quantitative research.
A correlation reflects the strength and/or direction of the association between two or more variables.
When an online source (e.g. web page, blog post) doesn’t list a publication date, you should instead list an access date.
Unlike a publication date, this appears at the end of your MLA Works Cited entry, after the URL, e.g. “A Complete Guide to MLA Style.” Scribbr, www.scribbr.com/category/mla/. Accessed 28 Mar. 2021.
For offline sources with no publication date shown, don’t use an access date—just leave out the date.
The level of detail you provide in a publication date in your Works Cited list depends on the type of source and the information available. Generally, follow the lead of the source—if it gives the full date, give the full date; if it gives just the year, so should you.
Books usually list the year, whereas web pages tend to give a full date. For journal articles, give the year, month and year, or season and year, depending on what information is available. Check our citation examples if you’re unsure about a particular source type.
In an MLA Works Cited list, the names of months with five or more letters are abbreviated to the first three letters, followed by a period. For example, abbreviate Feb., Mar., Apr., but not June, July.
In the main text, month names should never be abbreviated.
In your MLA Works Cited list, dates are always written in day-month-year order, with the month abbreviated if it’s five or more letters long, e.g. 5 Mar. 2018.
In the main text, you’re free to use either day-month-year or month-day-year order, as long as you use one or the other consistently. Don’t abbreviate months in the main text, and use numerals for dates, e.g. 5 March 2018 or March 5, 2018.
In the US, most graduate school applications require you to include:
Some programs may ask you to write a personal statement in addition to, or instead of, a statement of purpose. You may also be asked to an interview.
Always carefully read the application instructions for the specific program you’re applying to.
Some source types, such as books and journal articles, may contain footnotes (or endnotes) with additional information. MLA style provides guidelines for referring to information from a note in an in-text citation:
The director should always be listed in the author position in a Chicago film citation, followed by the label “director.” Other contributors to the film (actors, cinematographers, writers, composers, producers, etc.) may be listed after the film title, e.g. “Featuring Willem Dafoe and Robert Pattinson. Cinematography by Jarin Blaschke.”
Only the contributors relevant to your discussion of the film should be added. You might mention actors whose performances are discussed in detail, or the composer if the use of music in the film is examined. It’s also fine to mention no contributors other than the director, if none are relevant to your discussion.
In Chicago style, when a source does not include page numbers but you still want to point the reader to a specific point within it, an alternative locator should be used in your note or in-text citation. With audiovisual sources (e.g. films, videos, podcasts, songs), this is a timestamp, e.g. 1:15:28.
Web pages are usually short enough that no specific locator is needed. However, for a particularly long web page, you can use a subheading from the page, in quotation marks, e.g. “Citing Sources with Notes.”
Note that page numbers should be left out of newspaper citations, even when they are available. This is because page numbers can vary between different editions of a newspaper.
The purpose of a lab report is to demonstrate your understanding of the scientific method with a hands-on lab experiment. Course instructors will often provide you with an experimental design and procedure. Your task is to write up how you actually performed the experiment and evaluate the outcome.
In contrast, a research paper requires you to independently develop an original argument. It involves more in-depth research and interpretation of sources and data.
A lab report is usually shorter than a research paper.
The sections of a lab report can vary between scientific fields and course requirements, but it usually contains the following:
A lab report conveys the aim, methods, results, and conclusions of a scientific experiment. Lab reports are commonly assigned in science, technology, engineering, and mathematics (STEM) fields.
Random error is almost always present in scientific studies, even in highly controlled settings. While you can’t eradicate it completely, you can reduce random error by taking repeated measurements, using a large sample, and controlling extraneous variables.
You can avoid systematic error through careful design of your sampling, data collection, and analysis procedures. For example, use triangulation to measure your variables using multiple methods; regularly calibrate instruments or procedures; use random sampling and random assignment; and apply masking (blinding) where possible.
Systematic error is generally a bigger problem in research.
With random error, multiple measurements will tend to cluster around the true value. When you’re collecting data from a large sample, the errors in different directions will cancel each other out.
Systematic errors are much more problematic because they can skew your data away from the true value. This can lead you to false conclusions (Type I and II errors) about the relationship between the variables you’re studying.
Random and systematic error are two types of measurement error.
Random error is a chance difference between the observed and true values of something (e.g., a researcher misreading a weighing scale records an incorrect measurement).
Systematic error is a consistent or proportional difference between the observed and true values of something (e.g., a miscalibrated scale consistently records weights as higher than they actually are).
On graphs, the explanatory variable is conventionally placed on the x-axis, while the response variable is placed on the y-axis.
The term “explanatory variable” is sometimes preferred over “independent variable” because, in real world contexts, independent variables are often influenced by other variables. This means they aren’t totally independent.
Multiple independent variables may also be correlated with each other, so “explanatory variables” is a more appropriate term.
The difference between explanatory and response variables is simple:
In a controlled experiment, all extraneous variables are held constant so that they can’t influence the results. Controlled experiments require:
Depending on your study topic, there are various other methods of controlling variables.
In Chicago style, when you don’t just refer to an image but actually include it in your paper, the image should be formatted as a figure. Place the figure before or after the first paragraph where it is mentioned. Refer to figures by their numbers in the text (e.g. “see fig. 1”).
Below the figure, place a caption providing the figure number followed by a period (e.g. “Figure 1.”), a reference to the source (if you didn’t create the image yourself), and any relevant information to help the reader understand the image (if needed).
The caption is single-spaced and left-aligned, and followed by a blank line before the continuation of the main text.
There are 4 main types of extraneous variables:
An extraneous variable is any variable that you’re not investigating that can potentially affect the dependent variable of your research study.
A confounding variable is a type of extraneous variable that not only affects the dependent variable, but is also related to the independent variable.
According to the APA guidelines, you should report enough detail on inferential statistics so that your readers understand your analyses.
Report the following for each hypothesis test:
You should also present confidence intervals and estimates of effect sizes where relevant.
The number of decimal places to report depends on what you’re reporting. Generally, you should aim to round numbers while retaining precision. It’s best to present fewer decimal digits to aid easy understanding.
Use one decimal place for:
Use two decimal places for:
For a published interview (whether in video, audio, or print form), you should always include a citation, just as you would for any other source.
For an interview you conducted yourself, formally or informally, you often don’t need a citation and can just refer to it in the text or in a footnote, since the reader won’t be able to look them up anyway. MLA, however, still recommends including citations for your own interviews.
The main elements included in a newspaper interview citation across APA, MLA, and Chicago style are the names of the interviewer and interviewee, the interview title, the publication date, the name of the newspaper, and a URL (for online sources).
The information is presented differently in different citation styles. One key difference is that APA advises listing the interviewer in the author position, while MLA and Chicago advise listing the interviewee first.
In a factorial design, multiple independent variables are tested.
If you test two variables, each level of one independent variable is combined with each level of the other independent variable to create different conditions.
Within-subjects designs have many potential threats to internal validity, but they are also very statistically powerful.
Advantages:
Disadvantages:
Most medical school programs interview candidates, as do many (though not all) leading law and business schools.
In research programs, it depends—PhDs in business usually do, while those in economics normally do not, for example.
Some schools interview everyone, while others only interview their top candidates. Look at the websites of the schools you’re applying to for more information on whether they conduct interviews.
In addition to thinking about your answers for the most commonly asked grad school interview questions, you should reach out to former and current students to ask their advice on preparing and what sort of questions will be asked.
Look back through your resume and come up with anecdotes that you could use for common questions, particularly those that ask about obstacles that you overcame. If you’re applying for a research program, ensure that you can talk about the previous research experience you’ve had.
You should also read as much research in your field as possible. Research the faculty at the schools you’re applying to and read some of their papers. Come up with a few questions that you could ask them.
Graduate schools often ask questions about why you are interested in this particular program and what you will contribute.
Try to stay away from cliche answers like “this is a good program” or “I got good grades in undergrad” and focus instead on the unique strengths of the program or what you will bring to the table. Understand what the program is looking for and come up with anecdotes that demonstrate why you are a good fit for them.
Different types of programs may also focus on different questions:
The elements included in a newspaper article citation across APA, MLA, and Chicago style are the author name, the article title, the publication date, the newspaper name, and the URL if the article was accessed online.
In APA and MLA, the page numbers of the article appear in place of the URL if the article was accessed in print. No page numbers are used in Chicago newspaper citations.
Untitled sources (e.g. some images) are usually cited using a short descriptive text in place of the title. In APA Style, this description appears in brackets: [Chair of stained oak]. In MLA and Chicago styles, no brackets are used: Chair of stained oak.
For social media posts, which are usually untitled, quote the initial words of the post in place of the title: the first 160 characters in Chicago, or the first 20 words in APA. E.g. Biden, J. [@JoeBiden]. “The American Rescue Plan means a $7,000 check for a single mom of four. It means more support to safely.”
MLA recommends quoting the full post for something short like a tweet, and just describing the post if it’s longer.
The main elements included in image citations across APA, MLA, and Chicago style are the name of the image’s creator, the image title, the year (or more precise date) of publication, and details of the container in which the image was found (e.g. a museum, book, website).
In APA and Chicago style, it’s standard to also include a description of the image’s format (e.g. “Photograph” or “Oil on canvas”). This sort of information may be included in MLA too, but is not mandatory.
The main elements included in a lecture citation across APA, MLA, and Chicago style are the name of the speaker, the lecture title, the date it took place, the course or event it was part of, and the institution it took place at.
For transcripts or recordings of lectures/speeches, other details like the URL, the name of the book or website, and the length of the recording may be included instead of information about the event and institution.
The main elements included in a YouTube video citation across APA, MLA, and Chicago style are the name of the author/uploader, the title of the video, the publication date, and the URL.
The format in which this information appears is different for each style.
All styles also recommend using timestamps as a locator in the in-text citation or footnote.
While a between-subjects design has fewer threats to internal validity, it also requires more participants for high statistical power than a within-subjects design.
Advantages:
Disadvantages:
Yes. Between-subjects and within-subjects designs can be combined in a single study when you have two or more independent variables (a factorial design). In a mixed factorial design, one variable is altered between subjects and another is altered within subjects.
In a between-subjects design, every participant experiences only one condition, and researchers assess group differences between participants in various conditions.
In a within-subjects design, each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.
The word “between” means that you’re comparing different conditions between groups, while the word “within” means you’re comparing different conditions within the same group.
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Each annotation in an annotated bibliography is usually between 50 and 200 words long. Longer annotations may be divided into paragraphs.
The content of the annotation varies according to your assignment. An annotation can be descriptive, meaning it just describes the source objectively; evaluative, meaning it assesses its usefulness; or reflective, meaning it explains how the source will be used in your own research.
Any credible sources on your topic can be included in an annotated bibliography, but you should usually focus on collecting journal articles and scholarly books. When in doubt, utilize the CRAAP test!
An annotated bibliography is an assignment where you collect sources on a specific topic and write an annotation for each source. An annotation is a short text that describes and sometimes evaluates the source.
The elements included in journal article citations across APA, MLA, and Chicago style are the name(s) of the author(s), the title of the article, the year of publication, the name of the journal, the volume and issue numbers, the page range of the article, and, when accessed online, the DOI or URL.
In MLA and Chicago style, you also include the specific month or season of publication alongside the year, when this information is available.
Random assignment is used in experiments with a between-groups or independent measures design. In this research design, there’s usually a control group and one or more experimental groups. Random assignment helps ensure that the groups are comparable.
In general, you should always use random assignment in this type of experimental design when it is ethically possible and makes sense for your study topic.
To implement random assignment, assign a unique number to every member of your study’s sample.
Then, you can use a random number generator or a lottery method to randomly assign each number to a control or experimental group. You can also do so manually, by flipping a coin or rolling a dice to randomly assign participants to groups.
Random selection, or random sampling, is a way of selecting members of a population for your study’s sample.
In contrast, random assignment is a way of sorting the sample into control and experimental groups.
Random sampling enhances the external validity or generalizability of your results, while random assignment improves the internal validity of your study.
In experimental research, random assignment is a way of placing participants from your sample into different groups using randomization. With this method, every member of the sample has a known or equal chance of being placed in a control group or an experimental group.
The main elements included in website citations across APA, MLA, and Chicago style are the author, the date of publication, the page title, the website name, and the URL. The information is presented differently in each style.
“Controlling for a variable” means measuring extraneous variables and accounting for them statistically to remove their effects on other variables.
Researchers often model control variable data along with independent and dependent variable data in regression analyses and ANCOVAs. That way, you can isolate the control variable’s effects from the relationship between the variables of interest.
Control variables help you establish a correlational or causal relationship between variables by enhancing internal validity.
If you don’t control relevant extraneous variables, they may influence the outcomes of your study, and you may not be able to demonstrate that your results are really an effect of your independent variable.
A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.
Including mediators and moderators in your research helps you go beyond studying a simple relationship between two variables for a fuller picture of the real world. They are important to consider when studying complex correlational or causal relationships.
Mediators are part of the causal pathway of an effect, and they tell you how or why an effect takes place. Moderators usually help you judge the external validity of your study by identifying the limitations of when the relationship between variables holds.
If something is a mediating variable:
A confounder is a third variable that affects variables of interest and makes them seem related when they are not. In contrast, a mediator is the mechanism of a relationship between two variables: it explains the process by which they are related.
A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.
When you want to cite a specific passage in a source without page numbers (e.g. an e-book or website), all the main citation styles recommend using an alternate locator in your in-text citation. You might use a heading or chapter number, e.g. (Smith, 2016, ch. 1)
In APA Style, you can count the paragraph numbers in a text to identify a location by paragraph number. MLA and Chicago recommend that you only use paragraph numbers if they’re explicitly marked in the text.
For audiovisual sources (e.g. videos), all styles recommend using a timestamp to show a specific point in the video when relevant.
The abbreviation “et al.” (Latin for “and others”) is used to shorten citations of sources with multiple authors.
“Et al.” is used in APA in-text citations of sources with 3+ authors, e.g. (Smith et al., 2019). It is not used in APA reference entries.
Use “et al.” for 3+ authors in MLA in-text citations and Works Cited entries.
Use “et al.” for 4+ authors in a Chicago in-text citation, and for 10+ authors in a Chicago bibliography entry.
Check if your university or course guidelines specify which citation style to use. If the choice is left up to you, consider which style is most commonly used in your field.
Other more specialized styles exist for certain fields, such as Bluebook and OSCOLA for law.
The most important thing is to choose one style and use it consistently throughout your text.
The main elements included in all book citations across APA, MLA, and Chicago style are the author, the title, the year of publication, and the name of the publisher. A page number is also included in in-text citations to highlight the specific passage cited.
In Chicago style and in the 6th edition of APA Style, the location of the publisher is also included, e.g. London: Penguin.
There are various ways to improve power:
A power analysis is a calculation that helps you determine a minimum sample size for your study. It’s made up of four main components. If you know or have estimates for any three of these, you can calculate the fourth component.
Some students apply to graduate school straight from undergrad, but it’s also common to go back to school later in life. The ideal time to do so depends on various financial, personal, and career considerations. Graduate school is a big commitment, so you should apply at a time when you can devote your full attention to it.
Your career path may also determine when you should apply. In some career fields, you can easily progress without a graduate degree, while in others—such as medicine, business, and law—it’s virtually impossible to move up the career ladder without a specific graduate degree.
Most graduate school applications for American graduate programs are due in December or January for a September start.
Some types of programs, especially law school, are rolling applications, meaning that the earlier you apply, the earlier you’ll hear back. In this case, you should aim to apply as early as possible to maximize your chances.
Medical school follows a completely separate timeline with much earlier deadlines. If you’re applying for medical school, you should speak to advisors at your university for more information.
A good starting point to aim for is about 18 months before you would start the program, or 6–9 months before the applications are due.
In the first few months of the process, research programs and study for any standardized exams you might need.
You can then begin writing your personal statements and statements of purpose, as well as contacting people to write your letters of recommendation. Ensure that you give recommenders plenty of time to complete their letters (ideally around 2–4 months).
Null and alternative hypotheses are used in statistical hypothesis testing. The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.
Statistical analysis is the main method for analyzing quantitative research data. It uses probabilities and models to test predictions about a population from sample data.
No, including a URL is optional in APA Style reference entries for legal sources (e.g. court cases, laws). It can be useful to do so to aid the reader in retrieving the source, but it’s not required, since the other information included should be enough to locate it.
Generally, you should identify a law in an APA reference entry by its location in the United States Code (U.S.C.).
But if the law is either spread across various sections of the code or not featured in the code at all, include the public law number in addition to information on the source you accessed the law in, e.g.:
You should report methods using the past tense, even if you haven’t completed your study at the time of writing. That’s because the methods section is intended to describe completed actions or research.
In your APA methods section, you should report detailed information on the participants, materials, and procedures used.
For a stronger conclusion paragraph, avoid including:
Your conclusion should leave the reader with a strong, decisive impression of your work.
Your essay’s conclusion should contain:
The conclusion may also reflect on the broader implications of your argument, showing how your ideas could applied to other contexts or debates.
The conclusion paragraph of an essay is usually shorter than the introduction. As a rule, it shouldn’t take up more than 10–15% of the text.
With APA legal citations, it’s recommended to cite all the reporters (publications reporting cases) in which a court case appears. To cite multiple reporters, just separate them with commas in your reference entry. This is called parallel citation.
Don’t repeat the name of the case, court, or year; just list the volume, reporter, and page number for each citation. For example:
In APA Style, when you’re citing a recent court case that has not yet been reported in print and thus doesn’t have a specific page number, include a series of three underscores (___) where the page number would usually appear:
If you cite multiple Shakespeare plays throughout your MLA paper, the in-text citation begins with an abbreviated version of the title (as shown here), e.g. (Oth. 1.2.4). Each play should have its own Works Cited entry (even if they all come from the same collection).
If you cite only one Shakespeare play in your paper, you should include a Works Cited entry for that play, and your in-text citations should start with the author’s name, e.g. (Shakespeare 1.1.4).
No, do not use page numbers in your MLA in-text citations of Shakespeare plays. Instead, specify the act, scene, and line numbers of the quoted material, separated by periods, e.g. (Shakespeare 3.2.20–25).
This makes it easier for the reader to find the relevant passage in any edition of the text.
The risk of making a Type II error is inversely related to the statistical power of a test. Power is the extent to which a test can correctly detect a real effect when there is one.
To (indirectly) reduce the risk of a Type II error, you can increase the sample size or the significance level to increase statistical power.
The risk of making a Type I error is the significance level (or alpha) that you choose. That’s a value that you set at the beginning of your study to assess the statistical probability of obtaining your results (p value).
The significance level is usually set at 0.05 or 5%. This means that your results only have a 5% chance of occurring, or less, if the null hypothesis is actually true.
To reduce the Type I error probability, you can set a lower significance level.
In statistics, a Type I error means rejecting the null hypothesis when it’s actually true, while a Type II error means failing to reject the null hypothesis when it’s actually false.
When an article (e.g. in a newspaper) appears on non-consecutive pages (e.g. starting on page 1 and continuing on page 6), you should use “pp.” in your Works Cited entry, since it’s on multiple pages, but MLA recommends just listing the first page followed by a plus sign, e.g. pp. 1+.
In an MLA style Works Cited entry for a newspaper, you can cite a local newspaper in the same way as you would a national one, except that you may have to add the name of the city in square brackets to clarify what newspaper you mean, e.g. The Gazette [Montreal].
Do not add the city name in brackets if it’s already part of the newspaper’s name, e.g. Dallas Observer.
In statistics, power refers to the likelihood of a hypothesis test detecting a true effect if there is one. A statistically powerful test is more likely to reject a false negative (a Type II error).
If you don’t ensure enough power in your study, you may not be able to detect a statistically significant result even when it has practical significance. Your study might not have the ability to answer your research question.
While statistical significance shows that an effect exists in a study, practical significance shows that the effect is large enough to be meaningful in the real world.
Statistical significance is denoted by p-values whereas practical significance is represented by effect sizes.
There are dozens of measures of effect sizes. The most common effect sizes are Cohen’s d and Pearson’s r. Cohen’s d measures the size of the difference between two groups while Pearson’s r measures the strength of the relationship between two variables.
Effect size tells you how meaningful the relationship between variables or the difference between groups is.
A large effect size means that a research finding has practical significance, while a small effect size indicates limited practical applications.
In APA style, statistics can be presented in the main text or as tables or figures. To decide how to present numbers, you can follow APA guidelines:
Since these are general guidelines, use your own judgment and feedback from others for effective presentation of numbers.
In an APA results section, you should generally report the following:
Using descriptive and inferential statistics, you can make two types of estimates about the population: point estimates and interval estimates.
Both types of estimates are important for gathering a clear idea of where a parameter is likely to lie.
Standard error and standard deviation are both measures of variability. The standard deviation reflects variability within a sample, while the standard error estimates the variability across samples of a population.
The standard error of the mean, or simply standard error, indicates how different the population mean is likely to be from a sample mean. It tells you how much the sample mean would vary if you were to repeat a study using new samples from within a single population.
Like most style guides, APA recommends listing the book of the Bible you’re citing in your in-text citation, in combination with chapter and verse numbers. For example:
Books of the Bible may be abbreviated to save space; a list of standard abbreviations can be found here. Page numbers are not used in Bible citations.
Yes, in the 7th edition of APA Style, versions of the Bible are treated much like other books; you should include the edition you used in your reference list.
Previously, in the 6th edition of the APA manual, it was recommended to just use in-text citations to refer to the Bible, and omit it from the reference list.
MLA recommends citing the original source wherever possible, rather than the source in which it is quoted or reproduced.
If this isn’t possible, cite the secondary source and use “qtd. in” (quoted in) in your in-text citation. For example: (qtd. in Smith 233)
If a source is reproduced in full within another source (e.g. an image within a PowerPoint or a poem in an article), give details of the original source first, then include details of the secondary source as a container. For example:
When you want to cite a PowerPoint or lecture notes from a lecture you viewed in person in MLA, check whether they can also be accessed online; if so, this is the best version to cite, as it allows the reader to access the source.
If the material is not available online, use the details of where and when the presentation took place.
When you need to highlight a specific moment in a video or audio source, APA Style recommends using a timestamp in your in-text citation. Just include the timestamp from the start of the part you’re citing. For example:
In an MLA song citation, you need to give some sort of container to indicate how you accessed the song. If this is a physical or downloaded album, the Works Cited entry should list the album name, distributor, year, and format.
However, if you listened to the song on a streaming service, you can just list the site as a container, including a URL. In this case, including the album details is optional; you may add this information if it is relevant to your discussion or if it will help the reader access the song.
To figure out whether a given number is a parameter or a statistic, ask yourself the following:
If the answer is yes to both questions, the number is likely to be a parameter. For small populations, data can be collected from the whole population and summarized in parameters.
If the answer is no to either of the questions, then the number is more likely to be a statistic.
In the US, the graduate school application process is similar whether you’re applying for a master’s or a PhD. Both require letters of recommendation, a statement of purpose or personal statement, a resume or CV, and transcripts. Programs in the US and Canada usually also require a certain type of standardized test—often the GRE.
Outside the US, PhD programs usually also require applicants to write a research proposal, because students are expected to begin dissertation research in the first year of their PhD.
A master’s degree usually has a higher upfront cost, but it also allows you to start earning a higher salary more quickly. The exact cost depends on the country and the school: private universities usually cost more than public ones, and European degrees usually cost less than North American ones. There are limited possibilities for financial aid.
PhDs often waive tuition fees and offer a living stipend in exchange for a teaching or research assistantship. However, they take many years to complete, during which time you earn very little.
This depends on the country. In the United States, you can generally go directly to a PhD with only a bachelor’s degree, as a master’s program is included as part of the doctoral program.
Elsewhere, you generally need to graduate from a research-intensive master’s degree before continuing to the PhD.
This varies by country. In the United States, PhDs usually take between 5–7 years: 2 years of coursework followed by 3–5 years of independent research work to produce a dissertation.
In the rest of the world, students normally have a master’s degree before beginning the PhD, so they proceed directly to the research stage and complete a PhD in 3–5 years.
A PhD, which is short for philosophiae doctor (doctor of philosophy in Latin), is the highest university degree that can be obtained. In a PhD, students spend 3–5 years writing a dissertation, which aims to make a significant, original contribution to current knowledge.
A PhD is intended to prepare students for a career as a researcher, whether that be in academia, the public sector, or the private sector.
A master’s is a 1- or 2-year graduate degree that can prepare you for a variety of careers.
All master’s involve graduate-level coursework. Some are research-intensive and intend to prepare students for further study in a PhD; these usually require their students to write a master’s thesis. Others focus on professional training for a specific career.
To avoid plagiarism when summarizing an article or other source, follow these two rules:
A summary is always much shorter than the original text. The length of a summary can range from just a few sentences to several paragraphs; it depends on the length of the article you’re summarizing, and on the purpose of the summary.
A summary is a short overview of the main points of an article or other source, written entirely in your own words.
Whenever you refer to an image created by someone else in your text, you should include a citation leading the reader to the image you’re discussing.
If you include the image directly in your text as a figure, the details of the source appear in the figure’s caption. If you don’t, just include an in-text citation wherever you mention the image, and an entry in the Works Cited list giving full details.
The main guidelines for formatting a paper in Chicago style are to:
The main guidelines for formatting a paper in MLA style are as follows:
To format a paper in APA Style, follow these guidelines:
To include a direct quote in APA, follow these rules:
A block quote is a long quote formatted as a separate “block” of text. Instead of using quotation marks, you place the quote on a new line, and indent the entire quote to mark it apart from your own words.
The rules for when to apply block quote formatting depend on the citation style:
In academic writing, there are three main situations where quoting is the best choice:
Don’t overuse quotes; your own voice should be dominant. If you just want to provide information from a source, it’s usually better to paraphrase or summarize.
Every time you quote a source, you must include a correctly formatted in-text citation. This looks slightly different depending on the citation style.
For example, a direct quote in APA is cited like this: “This is a quote” (Streefkerk, 2020, p. 5).
Every in-text citation should also correspond to a full reference at the end of your paper.
A quote is an exact copy of someone else’s words, usually enclosed in quotation marks and credited to the original author or speaker.
APA doesn’t require you to include a list of tables or a list of figures. However, it is advisable to do so if your text is long enough to feature a table of contents and it includes a lot of tables and/or figures.
A list of tables and list of figures appear (in that order) after your table of contents, and are presented in a similar way.
Copyright information can usually be found wherever the table or figure was published. For example, for a diagram in a journal article, look on the journal’s website or the database where you found the article. Images found on sites like Flickr are listed with clear copyright information.
If you find that permission is required to reproduce the material, be sure to contact the author or publisher and ask for it.
If you adapt or reproduce a table or figure from another source, you should include that source in your APA reference list. You should also include copyright information in the note for the table or figure, and include an in-text citation when you refer to it.
Tables and figures you created yourself, based on your own data, are not included in the reference list.
An APA in-text citation is placed before the final punctuation mark in a sentence.
In an APA in-text citation, you use the phrase “as cited in” if you want to cite a source indirectly (i.e., if you cannot find the original source).
Parenthetical citation: (Brown, 1829, as cited in Mahone, 2018)
Narrative citation: Brown (1829, as cited in Mahone, 2018) states that…
On the reference page, you only include the secondary source (Mahone, 2018).
Popular word processors like Microsoft Word and Google Docs can order lists in alphabetical order, but they don’t follow the APA Style alphabetization guidelines.
If you use Scribbr’s APA Citation Generator to create citations, references are ordered automatically based on the APA guidelines, taking into account all the exceptions.
Order numerals as though they were spelled out:
Read more about alphabetizing the APA reference page.
It’s best to ask in person if possible, so first reach out and request a meeting to discuss your graduate school plans.
Let the potential recommender know which programs you’re applying to, and ask if they feel they can provide a strong letter of recommendation. A lukewarm recommendation can be the kiss of death for an application, so make sure your letter writers are enthusiastic about recommending you and your work!
Always remember to remain polite. Your recommenders are doing you a favor by taking the time to write a letter in support of your graduate school goals.
This depends on the program that you are applying for. Generally, for professional programs like business and policy school, you should ask managers who can speak to your future leadership potential and ability to succeed in your chosen career path.
However, in other graduate programs, you should mostly ask your former professors or research supervisors to write your recommendation letters, unless you have worked in a job that corresponds closely with your chosen field (e.g., as a full-time research assistant).
Choose people who know your work well and can speak to your ability to succeed in the program that you are applying to.
Remember, it is far more important to choose someone who knows you well than someone well-known. You may have taken classes with more prominent professors, but if they haven’t worked closely with you, they probably can’t write you a strong letter.
No, it’s not appropriate to present new arguments or evidence in the conclusion. While you might be tempted to save a striking argument for last, research papers follow a more formal structure than this.
All your findings and arguments should be presented in the body of the text (more specifically in the results and discussion sections if you are following a scientific structure). The conclusion is meant to summarize and reflect on the evidence and arguments you have already presented, not introduce new ones.
The conclusion of a research paper has several key elements you should make sure to include:
In MLA Style, you should cite a specific chapter or work within a book in two situations:
If you cite multiple chapters or works from the same book, include a separate Works Cited entry for each chapter.
Yes, if relevant you can and should include APA citations in your appendices. Use author-date citations as you do in the main text.
Any sources cited in your appendices should appear in your reference list. Do not create a separate reference list for your appendices.
Appendices in an APA Style paper appear right at the end, after the reference list and after your tables and figures if you’ve also included these at the end.
An appendix contains information that supplements the reader’s understanding of your research but is not essential to it. For example:
Something is only worth including as an appendix if you refer to information from it at some point in the text (e.g. quoting from an interview transcript). If you don’t, it should probably be removed.
The arithmetic mean is the most commonly used mean. It’s often simply called the mean or the average. But there are some other types of means you can calculate depending on your research purposes:
You can find the mean, or average, of a data set in two simple steps:
This method is the same whether you are dealing with sample or population data or positive or negative numbers.
An essay is a focused piece of writing that explains, argues, describes, or narrates.
In high school, you may have to write many different types of essays to develop your writing skills.
Academic essays at college level are usually argumentative: you develop a clear thesis about your topic and make a case for your position using evidence, analysis and interpretation.
The “hook” is the first sentence of your essay introduction. It should lead the reader into your essay, giving a sense of why it’s interesting.
To write a good hook, avoid overly broad statements or long, dense sentences. Try to start with something clear, concise and catchy that will spark your reader’s curiosity.
Your essay introduction should include three main things, in this order:
The length of each part depends on the length and complexity of your essay.
The median is the most informative measure of central tendency for skewed distributions or distributions with outliers. For example, the median is often used as a measure of central tendency for income distributions, which are generally highly skewed.
Because the median only uses one or two values, it’s unaffected by extreme outliers or non-symmetric distributions of scores. In contrast, the mean and mode can vary in skewed distributions.
To find the median, first order your data. Then calculate the middle position based on n, the number of values in your data set.
A data set can often have no mode, one mode or more than one mode – it all depends on how many different values repeat most frequently.
Your data can be:
To find the mode:
Then you simply need to identify the most frequently occurring value.
There are three key steps in systematic sampling:
Systematic sampling is a probability sampling method where researchers select members of the population at a regular interval – for example, by selecting every 15th person on a list of the population. If the population is in a random order, this can imitate the benefits of simple random sampling.
Let’s say you’re writing a five-paragraph essay about the environmental impacts of dietary choices. Here are three examples of topic sentences you could use for each of the three body paragraphs:
Each of these sentences expresses one main idea – by listing them in order, we can see the overall structure of the essay at a glance. Each paragraph will expand on the topic sentence with relevant detail, evidence, and arguments.
The topic sentence usually comes at the very start of the paragraph.
However, sometimes you might start with a transition sentence to summarize what was discussed in previous paragraphs, followed by the topic sentence that expresses the focus of the current paragraph.
Topic sentences help keep your writing focused and guide the reader through your argument.
In an essay or paper, each paragraph should focus on a single idea. By stating the main idea in the topic sentence, you clarify what the paragraph is about for both yourself and your reader.
A topic sentence is a sentence that expresses the main point of a paragraph. Everything else in the paragraph should relate to the topic sentence.
The interquartile range is the best measure of variability for skewed distributions or data sets with outliers. Because it’s based on values that come from the middle half of the distribution, it’s unlikely to be influenced by outliers.
The two most common methods for calculating interquartile range are the exclusive and inclusive methods.
The exclusive method excludes the median when identifying Q1 and Q3, while the inclusive method includes the median as a value in the data set in identifying the quartiles.
For each of these methods, you’ll need different procedures for finding the median, Q1 and Q3 depending on whether your sample size is even- or odd-numbered. The exclusive method works best for even-numbered sample sizes, while the inclusive method is often used with odd-numbered sample sizes.
While the range gives you the spread of the whole data set, the interquartile range gives you the spread of the middle half of a data set.
Don’t feel that you have to write the introduction first. The introduction is often one of the last parts of the research paper you’ll write, along with the conclusion.
This is because it can be easier to introduce your paper once you’ve already written the body; you may not have the clearest idea of your arguments until you’ve written them, and things can change during the writing process.
The way you present your research problem in your introduction varies depending on the nature of your research paper. A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement.
A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis—a prediction that will be confirmed or disproved by your research.
The introduction of a research paper includes several key elements:
Homoscedasticity, or homogeneity of variances, is an assumption of equal or similar variances in different groups being compared.
This is an important assumption of parametric statistical tests because they are sensitive to any dissimilarities. Uneven variances in samples result in biased and skewed test results.
Statistical tests such as variance tests or the analysis of variance (ANOVA) use sample variance to assess group differences of populations. They use the variances of the samples to assess whether the populations they come from significantly differ from each other.
Yes, you can create a stratified sample using multiple characteristics, but you must ensure that every participant in your study belongs to one and only one subgroup. In this case, you multiply the numbers of subgroups for each characteristic to get the total number of groups.
For example, if you were stratifying by location with three subgroups (urban, rural, or suburban) and marital status with five subgroups (single, divorced, widowed, married, or partnered), you would have 3 x 5 = 15 subgroups.
You should use stratified sampling when your sample can be divided into mutually exclusive and exhaustive subgroups that you believe will take on different mean values for the variable that you’re studying.
Using stratified sampling will allow you to obtain more precise (with lower variance) statistical estimates of whatever you are trying to measure.
For example, say you want to investigate how income differs based on educational attainment, but you know that this relationship can vary based on race. Using stratified sampling, you can ensure you obtain a large enough sample from each racial group, allowing you to draw more precise conclusions.
In stratified sampling, researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment, etc).
Once divided, each subgroup is randomly sampled using another probability sampling method.
The thesis statement is essential in any academic essay or research paper for two main reasons:
Without a clear thesis, an essay can end up rambling and unfocused, leaving your reader unsure of exactly what you want to say.
The thesis statement should be placed at the end of your essay introduction.
A thesis statement is a sentence that sums up the central point of your paper or essay. Everything else you write should relate to this key idea.
An essay isn’t just a loose collection of facts and ideas. Instead, it should be centered on an overarching argument (summarized in your thesis statement) that every part of the essay relates to.
The way you structure your essay is crucial to presenting your argument coherently. A well-structured essay helps your reader follow the logic of your ideas and understand your overall point.
The structure of an essay is divided into an introduction that presents your topic and thesis statement, a body containing your in-depth analysis and arguments, and a conclusion wrapping up your ideas.
The structure of the body is flexible, but you should always spend some time thinking about how you can organize your essay to best serve your ideas.
Variance is the average squared deviations from the mean, while standard deviation is the square root of this number. Both measures reflect variability in a distribution, but their units differ:
Although the units of variance are harder to intuitively understand, variance is important in statistical tests.
The empirical rule, or the 68-95-99.7 rule, tells you where most of the values lie in a normal distribution:
The empirical rule is a quick way to get an overview of your data and check for any outliers or extreme values that don’t follow this pattern.
In a normal distribution, data is symmetrically distributed with no skew. Most values cluster around a central region, with values tapering off as they go further away from the center.
The measures of central tendency (mean, mode and median) are exactly the same in a normal distribution.
The standard deviation is the average amount of variability in your data set. It tells you, on average, how far each score lies from the mean.
In normal distributions, a high standard deviation means that values are generally far from the mean, while a low standard deviation indicates that values are clustered close to the mean.
In a thesis or dissertation, the discussion is an in-depth exploration of the results, going into detail about the meaning of your findings and citing relevant sources to put them in context.
The conclusion is more shorter and more general: it concisely answers your main research question and makes recommendations based on your overall findings.
In the discussion, you explore the meaning and relevance of your research results, explaining how they fit with existing research and theory. Discuss:
The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.
In qualitative research, results and discussion are sometimes combined. But in quantitative research, it’s considered important to separate the objective results from your interpretation of them.
Results are usually written in the past tense, because they are describing the outcome of completed actions.
The results chapter of a thesis or dissertation presents your research results concisely and objectively.
In quantitative research, for each question or hypothesis, state:
In qualitative research, for each question or theme, describe:
Don’t interpret or speculate in the results chapter.
No. Because the range formula subtracts the lowest number from the highest number, the range is always zero or a positive number.
In statistics, the range is the spread of your data from the lowest to the highest value in the distribution. It is the simplest measure of variability.
Cluster sampling is more time- and cost-efficient than other probability sampling methods, particularly when it comes to large samples spread across a wide geographical area.
However, it provides less statistical certainty than other methods, such as simple random sampling, because it is difficult to ensure that your clusters properly represent the population as a whole.
There are three types of cluster sampling: single-stage, double-stage and multi-stage clustering. In all three types, you first divide the population into clusters, then randomly select clusters for use in your sample.
Cluster sampling is a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample.
The clusters should ideally each be mini-representations of the population as a whole.
While central tendency tells you where most of your data points lie, variability summarizes how far apart your points from each other.
Data sets can have the same central tendency but different levels of variability or vice versa. Together, they give you a complete picture of your data.
Variability is most commonly measured with the following descriptive statistics:
Variability tells you how far apart points lie from each other and from the center of a distribution or a data set.
Variability is also referred to as spread, scatter or dispersion.
The vast majority of essays written at university are some sort of argumentative essay. Almost all academic writing involves building up an argument, though other types of essay might be assigned in composition classes.
Essays can present arguments about all kinds of different topics. For example:
At high school and in composition classes at university, you’ll often be told to write a specific type of essay, but you might also just be given prompts.
Look for keywords in these prompts that suggest a certain approach: The word “explain” suggests you should write an expository essay, while the word “describe” implies a descriptive essay. An argumentative essay might be prompted with the word “assess” or “argue.”
While interval and ratio data can both be categorized, ranked, and have equal spacing between adjacent values, only ratio scales have a true zero.
For example, temperature in Celsius or Fahrenheit is at an interval scale because zero is not the lowest possible temperature. In the Kelvin scale, a ratio scale, zero represents a total lack of thermal energy.
In rhetorical analysis, a claim is something the author wants the audience to believe. A support is the evidence or appeal they use to convince the reader to believe the claim. A warrant is the (often implicit) assumption that links the support with the claim.
Logos appeals to the audience’s reason, building up logical arguments. Ethos appeals to the speaker’s status or authority, making the audience more likely to trust them. Pathos appeals to the emotions, trying to make the audience feel angry or sympathetic, for example.
Collectively, these three appeals are sometimes called the rhetorical triangle. They are central to rhetorical analysis, though a piece of rhetoric might not necessarily use all of them.
The term “text” in a rhetorical analysis essay refers to whatever object you’re analyzing. It’s frequently a piece of writing or a speech, but it doesn’t have to be. For example, you could also treat an advertisement or political cartoon as a text.
The goal of a rhetorical analysis is to explain the effect a piece of writing or oratory has on its audience, how successful it is, and the devices and appeals it uses to achieve its goals.
Unlike a standard argumentative essay, it’s less about taking a position on the arguments presented, and more about exploring how they are constructed.
A critical value is the value of the test statistic which defines the upper and lower bounds of a confidence interval, or which defines the threshold of statistical significance in a statistical test. It describes how far from the mean of the distribution you have to go to cover a certain amount of the total variation in the data (i.e. 90%, 95%, 99%).
If you are constructing a 95% confidence interval and are using a threshold of statistical significance of p = 0.05, then your critical value will be identical in both cases.
The t-distribution gives more probability to observations in the tails of the distribution than the standard normal distribution (a.k.a. the z-distribution).
In this way, the t-distribution is more conservative than the standard normal distribution: to reach the same level of confidence or statistical significance, you will need to include a wider range of the data.
A t-score (a.k.a. a t-value) is equivalent to the number of standard deviations away from the mean of the t-distribution.
The t-score is the test statistic used in t-tests and regression tests. It can also be used to describe how far from the mean an observation is when the data follow a t-distribution.
The t-distribution is a way of describing a set of observations where most observations fall close to the mean, and the rest of the observations make up the tails on either side. It is a type of normal distribution used for smaller sample sizes, where the variance in the data is unknown.
The t-distribution forms a bell curve when plotted on a graph. It can be described mathematically using the mean and the standard deviation.
If properly implemented, simple random sampling is usually the best sampling method for ensuring both internal and external validity. However, it can sometimes be impractical and expensive to implement, depending on the size of the population to be studied,
If you have a list of every member of the population and the ability to reach whichever members are selected, you can use simple random sampling.
The American Community Survey is an example of simple random sampling. In order to collect detailed data on the population of the US, the Census Bureau officials randomly select 3.5 million households per year and use a variety of methods to convince them to fill out the survey.
Simple random sampling is a type of probability sampling in which the researcher randomly selects a subset of participants from a population. Each member of the population has an equal chance of being selected. Data is then collected from as large a percentage as possible of this random subset.
You should try to follow your outline as you write your essay. However, if your ideas change or it becomes clear that your structure could be better, it’s okay to depart from your essay outline. Just make sure you know why you’re doing so.
If you have to hand in your essay outline, you may be given specific guidelines stating whether you have to use full sentences. If you’re not sure, ask your supervisor.
When writing an essay outline for yourself, the choice is yours. Some students find it helpful to write out their ideas in full sentences, while others prefer to summarize them in short phrases.
You will sometimes be asked to hand in an essay outline before you start writing your essay. Your supervisor wants to see that you have a clear idea of your structure so that writing will go smoothly.
Even when you do not have to hand it in, writing an essay outline is an important part of the writing process. It’s a good idea to write one (as informally as you like) to clarify your structure for yourself whenever you are working on an essay.
In statistics, ordinal and nominal variables are both considered categorical variables.
Even though ordinal data can sometimes be numerical, not all mathematical operations can be performed on them.
Ordinal data has two characteristics:
However, unlike with interval data, the distances between the categories are uneven or unknown.
To automatically insert a table of contents in Microsoft Word, follow these steps:
Make sure to update your table of contents if you move text or change headings. To update, simply right click and select Update Field.
All level 1 and 2 headings should be included in your table of contents. That means the titles of your chapters and the main sections within them.
The contents should also include all appendices and the lists of tables and figures, if applicable, as well as your reference list.
Do not include the acknowledgements or abstract in the table of contents.
Nominal and ordinal are two of the four levels of measurement. Nominal level data can only be classified, while ordinal level data can be classified and ordered.
Nominal data is data that can be labelled or classified into mutually exclusive categories within a variable. These categories cannot be ordered in a meaningful way.
For example, for the nominal variable of preferred mode of transportation, you may have the categories of car, bus, train, tram or bicycle.
If your confidence interval for a difference between groups includes zero, that means that if you run your experiment again you have a good chance of finding no difference between groups.
If your confidence interval for a correlation or regression includes zero, that means that if you run your experiment again there is a good chance of finding no correlation in your data.
In both of these cases, you will also find a high p-value when you run your statistical test, meaning that your results could have occurred under the null hypothesis of no relationship between variables or no difference between groups.
If you want to calculate a confidence interval around the mean of data that is not normally distributed, you have two choices:
The standard normal distribution, also called the z-distribution, is a special normal distribution where the mean is 0 and the standard deviation is 1.
Any normal distribution can be converted into the standard normal distribution by turning the individual values into z-scores. In a z-distribution, z-scores tell you how many standard deviations away from the mean each value lies.
The z-score and t-score (aka z-value and t-value) show how many standard deviations away from the mean of the distribution you are, assuming your data follow a z-distribution or a t-distribution.
These scores are used in statistical tests to show how far from the mean of the predicted distribution your statistical estimate is. If your test produces a z-score of 2.5, this means that your estimate is 2.5 standard deviations from the predicted mean.
The predicted mean and distribution of your estimate are generated by the null hypothesis of the statistical test you are using. The more standard deviations away from the predicted mean your estimate is, the less likely it is that the estimate could have occurred under the null hypothesis.
To calculate the confidence interval, you need to know:
Then you can plug these components into the confidence interval formula that corresponds to your data. The formula depends on the type of estimate (e.g. a mean or a proportion) and on the distribution of your data.
The confidence level is the percentage of times you expect to get close to the same estimate if you run your experiment again or resample the population in the same way.
The confidence interval consists of the upper and lower bounds of the estimate you expect to find at a given level of confidence.
For example, if you are estimating a 95% confidence interval around the mean proportion of female babies born every year based on a random sample of babies, you might find an upper bound of 0.56 and a lower bound of 0.48. These are the upper and lower bounds of the confidence interval. The confidence level is 95%.
This means that 95% of the calculated confidence intervals (for this sample) contains the true mean of the population.
The abstract appears on its own page, after the title page and acknowledgements but before the table of contents.
An abstract for a thesis or dissertation is usually around 200–300 words. There’s often a strict word limit, so make sure to check your university’s requirements.
In a thesis or dissertation, the acknowledgements should usually be no longer than one page. There is no minimum length.
The acknowledgements are generally included at the very beginning of your thesis, directly after the title page and before the abstract.
Yes, it’s important to thank your supervisor(s) in the acknowledgements section of your thesis or dissertation.
Even if you feel your supervisor did not contribute greatly to the final product, you must acknowledge them, if only for a very brief thank you. If you do not include your supervisor, it may be seen as a snub.
In the acknowledgements of your thesis or dissertation, you should first thank those who helped you academically or professionally, such as your supervisor, funders, and other academics.
Then you can include personal thanks to friends, family members, or anyone else who supported you during the process.
Comparisons in essays are generally structured in one of two ways:
It’s also possible to combine both methods, for example by writing a full paragraph on each of your topics and then a final paragraph contrasting the two according to a specific metric.
Your subjects might be very different or quite similar, but it’s important that there be meaningful grounds for comparison. You can probably describe many differences between a cat and a bicycle, but there isn’t really any connection between them to justify the comparison.
You’ll have to write a thesis statement explaining the central point you want to make in your essay, so be sure to know in advance what connects your subjects and makes them worth comparing.
Some essay prompts include the keywords “compare” and/or “contrast.” In these cases, an essay structured around comparing and contrasting is the appropriate response.
Comparing and contrasting is also a useful approach in all kinds of academic writing: You might compare different studies in a literature review, weigh up different arguments in an argumentative essay, or consider different theoretical approaches in a theoretical framework.
Quasi-experimental design is most useful in situations where it would be unethical or impractical to run a true experiment.
Quasi-experiments have lower internal validity than true experiments, but they often have higher external validity as they can use real-world interventions instead of artificial laboratory settings.
A quasi-experiment is a type of research design that attempts to establish a cause-and-effect relationship. The main difference with a true experiment is that the groups are not randomly assigned.
The key difference is that a narrative essay is designed to tell a complete story, while a descriptive essay is meant to convey an intense description of a particular place, object, or concept.
Narrative and descriptive essays both allow you to write more personally and creatively than other kinds of essays, and similar writing skills can apply to both.
If you’re not given a specific prompt for your descriptive essay, think about places and objects you know well, that you can think of interesting ways to describe, or that have strong personal significance for you.
The best kind of object for a descriptive essay is one specific enough that you can describe its particular features in detail—don’t choose something too vague or general.
The mean is the most frequently used measure of central tendency because it uses all values in the data set to give you an average.
For data from skewed distributions, the median is better than the mean because it isn’t influenced by extremely large values.
The mode is the only measure you can use for nominal or categorical data that can’t be ordered.
The measures of central tendency you can use depends on the level of measurement of your data.
Measures of central tendency help you find the middle, or the average, of a data set.
The 3 most common measures of central tendency are the mean, median and mode.
If you’re not given much guidance on what your narrative essay should be about, consider the context and scope of the assignment. What kind of story is relevant, interesting, and possible to tell within the word count?
The best kind of story for a narrative essay is one you can use to reflect on a particular theme or lesson, or that takes a surprising turn somewhere along the way.
Don’t worry too much if your topic seems unoriginal. The point of a narrative essay is how you tell the story and the point you make with it, not the subject of the story itself.
Narrative essays are usually assigned as writing exercises at high school or in university composition classes. They may also form part of a university application.
When you are prompted to tell a story about your own life or experiences, a narrative essay is usually the right response.
The majority of the essays written at university are some sort of argumentative essay. Unless otherwise specified, you can assume that the goal of any essay you’re asked to write is argumentative: To convince the reader of your position using evidence and reasoning.
In composition classes you might be given assignments that specifically test your ability to write an argumentative essay. Look out for prompts including instructions like “argue,” “assess,” or “discuss” to see if this is the goal.
At college level, you must properly cite your sources in all essays, research papers, and other academic texts (except exams and in-class exercises).
Add a citation whenever you quote, paraphrase, or summarize information or ideas from a source. You should also give full source details in a bibliography or reference list at the end of your text.
The exact format of your citations depends on which citation style you are instructed to use. The most common styles are APA, MLA, and Chicago.
Some variables have fixed levels. For example, gender and ethnicity are always nominal level data because they cannot be ranked.
However, for other variables, you can choose the level of measurement. For example, income is a variable that can be recorded on an ordinal or a ratio scale:
If you have a choice, the ratio level is always preferable because you can analyze data in more ways. The higher the level of measurement, the more precise your data is.
The level at which you measure a variable determines how you can analyze your data.
Depending on the level of measurement, you can perform different descriptive statistics to get an overall summary of your data and inferential statistics to see if your results support or refute your hypothesis.
Levels of measurement tell you how precisely variables are recorded. There are 4 levels of measurement, which can be ranked from low to high:
No. The p-value only tells you how likely the data you have observed is to have occurred under the null hypothesis.
If the p-value is below your threshold of significance (typically p < 0.05), then you can reject the null hypothesis, but this does not necessarily mean that your alternative hypothesis is true.
The alpha value, or the threshold for statistical significance, is arbitrary – which value you use depends on your field of study.
In most cases, researchers use an alpha of 0.05, which means that there is a less than 5% chance that the data being tested could have occurred under the null hypothesis.
P-values are usually automatically calculated by the program you use to perform your statistical test. They can also be estimated using p-value tables for the relevant test statistic.
P-values are calculated from the null distribution of the test statistic. They tell you how often a test statistic is expected to occur under the null hypothesis of the statistical test, based on where it falls in the null distribution.
If the test statistic is far from the mean of the null distribution, then the p-value will be small, showing that the test statistic is not likely to have occurred under the null hypothesis.
A p-value, or probability value, is a number describing how likely it is that your data would have occurred under the null hypothesis of your statistical test.
The test statistic you use will be determined by the statistical test.
You can choose the right statistical test by looking at what type of data you have collected and what type of relationship you want to test.
The test statistic will change based on the number of observations in your data, how variable your observations are, and how strong the underlying patterns in the data are.
For example, if one data set has higher variability while another has lower variability, the first data set will produce a test statistic closer to the null hypothesis, even if the true correlation between two variables is the same in either data set.
The formula for the test statistic depends on the statistical test being used.
Generally, the test statistic is calculated as the pattern in your data (i.e. the correlation between variables or difference between groups) divided by the variance in the data (i.e. the standard deviation).
An argumentative essay tends to be a longer essay involving independent research, and aims to make an original argument about a topic. Its thesis statement makes a contentious claim that must be supported in an objective, evidence-based way.
An expository essay also aims to be objective, but it doesn’t have to make an original argument. Rather, it aims to explain something (e.g., a process or idea) in a clear, concise way. Expository essays are often shorter assignments and rely less on research.
An expository essay is a common assignment in high-school and university composition classes. It might be assigned as coursework, in class, or as part of an exam.
Sometimes you might not be told explicitly to write an expository essay. Look out for prompts containing keywords like “explain” and “define.” An expository essay is usually the right response to these prompts.
An expository essay is a broad form that varies in length according to the scope of the assignment.
Expository essays are often assigned as a writing exercise or as part of an exam, in which case a five-paragraph essay of around 800 words may be appropriate.
You’ll usually be given guidelines regarding length; if you’re not sure, ask.
Blinding is important to reduce bias (e.g., observer bias, demand characteristics) and ensure a study’s internal validity.
If participants know whether they are in a control or treatment group, they may adjust their behavior in ways that affect the outcome that researchers are trying to measure. If the people administering the treatment are aware of group assignment, they may treat participants differently and thus directly or indirectly influence the final results.
Blinding means hiding who is assigned to the treatment group and who is assigned to the control group in an experiment.
The 3 main types of descriptive statistics concern the frequency distribution, central tendency, and variability of a dataset.
Descriptive statistics summarize the characteristics of a data set. Inferential statistics allow you to test a hypothesis or assess whether your data is generalizable to the broader population.
A true experiment (a.k.a. a controlled experiment) always includes at least one control group that doesn’t receive the experimental treatment.
However, some experiments use a within-subjects design to test treatments without a control group. In these designs, you usually compare one group’s outcomes before and after a treatment (instead of comparing outcomes between different groups).
For strong internal validity, it’s usually best to include a control group if possible. Without a control group, it’s harder to be certain that the outcome was caused by the experimental treatment and not by other variables.
An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.
Individual Likert-type questions are generally considered ordinal data, because the items have clear rank order, but don’t have an even distribution.
Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.
The type of data determines what statistical tests you should use to analyze your data.
A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. It is made up of 4 or more questions that measure a single attitude or trait when response scores are combined.
To use a Likert scale in a survey, you present participants with Likert-type questions or statements, and a continuum of items, usually with 5 or 7 possible responses, to capture their degree of agreement.
In scientific research, concepts are the abstract ideas or phenomena that are being studied (e.g., educational achievement). Variables are properties or characteristics of the concept (e.g., performance at school), while indicators are ways of measuring or quantifying variables (e.g., yearly grade reports).
The process of turning abstract concepts into measurable variables and indicators is called operationalization.
There are various approaches to qualitative data analysis, but they all share five steps in common:
The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis, thematic analysis, and discourse analysis.
There are five common approaches to qualitative research:
Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses, by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.
When an online source does not list a publication date, replace it with an access date in your in footnote citations and your bibliography:
If you are using author-date in-text citations, or if the source was not accessed online, replace the date with “n.d.”
Operationalization means turning abstract conceptual ideas into measurable observations.
For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.
Before collecting data, it’s important to consider how you will operationalize the variables that you want to measure.
When conducting research, collecting original data has significant advantages:
However, there are also some drawbacks: data collection can be time-consuming, labor-intensive and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.
Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.
There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control and randomization.
In restriction, you restrict your sample by only including certain subjects that have the same values of potential confounding variables.
In matching, you match each of the subjects in your treatment group with a counterpart in the comparison group. The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable.
In statistical control, you include potential confounders as variables in your regression.
In randomization, you randomly assign the treatment (or independent variable) in your study to a sufficiently large number of subjects, which allows you to control for all potential confounding variables.
A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed cause, while the dependent variable is the supposed effect. A confounding variable is a third variable that influences both the independent and dependent variables.
Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.
To ensure the internal validity of your research, you must consider the impact of confounding variables. If you fail to account for them, you might over- or underestimate the causal relationship between your independent and dependent variables, or even find a causal relationship where none exists.
Yes, but including more than one of either type requires multiple research questions.
For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.
You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable.
To ensure the internal validity of an experiment, you should only change one independent variable at a time.
No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both!
You want to find out how blood sugar levels are affected by drinking diet soda and regular soda, so you conduct an experiment.
Determining cause and effect is one of the most important parts of scientific research. It’s essential to know which is the cause – the independent variable – and which is the effect – the dependent variable.
In non-probability sampling, the sample is selected based on non-random criteria, and not every member of the population has a chance of being included.
Common non-probability sampling methods include convenience sampling, voluntary response sampling, purposive sampling, snowball sampling, and quota sampling.
Probability sampling means that every member of the target population has a known chance of being included in the sample.
Probability sampling methods include simple random sampling, systematic sampling, stratified sampling, and cluster sampling.
Using careful research design and sampling procedures can help you avoid sampling bias. Oversampling can be used to correct undercoverage bias.
Some common types of sampling bias include self-selection, non-response, undercoverage, survivorship, pre-screening or advertising, and healthy user bias.
Sampling bias is a threat to external validity – it limits the generalizability of your findings to a broader group of people.
Sampling bias occurs when some members of a population are systematically more likely to be selected in a sample than others.
A sampling error is the difference between a population parameter and a sample statistic.
A statistic refers to measures about the sample, while a parameter refers to measures about the population.
Populations are used when a research question requires data from every member of the population. This is usually only feasible when the population is small and easily accessible.
Samples are used to make inferences about populations. Samples are easier to collect data from because they are practical, cost-effective, convenient and manageable.
You must include an in-text citation every time you quote or paraphrase from a source (e.g. a book, movie, website, or article).
There are seven threats to external validity: selection bias, history, experimenter effect, Hawthorne effect, testing effect, aptitude-treatment and situation effect.
The two types of external validity are population validity (whether you can generalize to other groups of people) and ecological validity (whether you can generalize to other situations and settings).
The external validity of a study is the extent to which you can generalize your findings to different groups of people, situations, and measures.
Cross-sectional studies cannot establish a cause-and-effect relationship or analyze behavior over a period of time. To investigate cause and effect, you need to do a longitudinal study or an experimental study.
Cross-sectional studies are less expensive and time-consuming than many other types of study. They can provide useful insights into a population’s characteristics and identify correlations for further research.
Sometimes only cross-sectional data is available for analysis; other times your research question may only require a cross-sectional study to answer it.
Longitudinal studies can last anywhere from weeks to decades, although they tend to be at least a year long.
The 1970 British Cohort Study, which has collected data on the lives of 17,000 Brits since their births in 1970, is one well-known example of a longitudinal study.
Longitudinal studies are better to establish the correct sequence of events, identify changes over time, and provide insight into cause-and-effect relationships, but they also tend to be more expensive and time-consuming than other types of studies.
Longitudinal studies and cross-sectional studies are two different types of research design. In a cross-sectional study you collect data from a population at a specific point in time; in a longitudinal study you repeatedly collect data from the same sample over an extended period of time.
| Longitudinal study | Cross-sectional study |
|---|---|
| Repeated observations | Observations at a single point in time |
| Observes the same group multiple times | Observes different groups (a “cross-section”) in the population |
| Follows changes in participants over time | Provides snapshot of society at a given point |
There are eight threats to internal validity: history, maturation, instrumentation, testing, selection bias, regression to the mean, social interaction and attrition.
Internal validity is the extent to which you can be confident that a cause-and-effect relationship established in a study cannot be explained by other factors.
If you’ve gone over the word limit set for your assignment, shorten your sentences and cut repetition and redundancy during the editing process. If you use a lot of long quotes, consider shortening them to just the essentials.
If you need to remove a lot of words, you may have to cut certain passages. Remember that everything in the text should be there to support your argument; look for any information that’s not essential to your point and remove it.
Revising, proofreading, and editing are different stages of the writing process.
In statistics, model selection is a process researchers use to compare the relative value of different statistical models and determine which one is the best fit for the observed data.
The Akaike information criterion is one of the most common methods of model selection. AIC weights the ability of the model to predict the observed data against the number of parameters the model requires to reach that level of precision.
AIC model selection can help researchers find a model that explains the observed variation in their data while avoiding overfitting.
In statistics, a model is the collection of one or more independent variables and their predicted interactions that researchers use to try to explain variation in their dependent variable.
You can test a model using a statistical test. To compare how well different models fit your data, you can use Akaike’s information criterion for model selection.
The Akaike information criterion is calculated from the maximum log-likelihood of the model and the number of parameters (K) used to reach that likelihood. The AIC function is 2K – 2(log-likelihood).
Lower AIC values indicate a better-fit model, and a model with a delta-AIC (the difference between the two AIC values being compared) of more than -2 is considered significantly better than the model it is being compared to.
The Akaike information criterion is a mathematical test used to evaluate how well a model fits the data it is meant to describe. It penalizes models which use more independent variables (parameters) as a way to avoid over-fitting.
AIC is most often used to compare the relative goodness-of-fit among different models under consideration and to then choose the model that best fits the data.
If you adapt or reproduce a table or figure from another source, you should include that source in your APA reference list. You should also acknowledge the original source in the note or caption for the table or figure.
Tables and figures you created yourself, based on your own data, are not included in the reference list.
APA doesn’t require you to include a list of tables or a list of figures. However, it is advisable to do so if your text is long enough to feature a table of contents and it includes a lot of tables and/or figures.
A list of tables and list of figures appear (in that order) after your table of contents, and are presented in a similar way.
In an APA Style paper, use a table or figure when it’s a clearer way to present important data than describing it in your main text. This is often the case when you need to communicate a large amount of information.
Before including a table or figure in your text, always reflect on whether it’s useful to your readers’ understanding:
If the data you need to present only contains a few relevant numbers, try summarizing it in the text (potentially including full data in an appendix). If describing the data makes your text overly long and difficult to read, a table or figure may be the best option.
A factorial ANOVA is any ANOVA that uses more than one categorical independent variable. A two-way ANOVA is a type of factorial ANOVA.
Some examples of factorial ANOVAs include:
In ANOVA, the null hypothesis is that there is no difference among group means. If any group differs significantly from the overall group mean, then the ANOVA will report a statistically significant result.
Significant differences among group means are calculated using the F statistic, which is the ratio of the mean sum of squares (the variance explained by the independent variable) to the mean square error (the variance left over).
If the F statistic is higher than the critical value (the value of F that corresponds with your alpha value, usually 0.05), then the difference among groups is deemed statistically significant.
The only difference between one-way and two-way ANOVA is the number of independent variables. A one-way ANOVA has one independent variable, while a two-way ANOVA has two.
All ANOVAs are designed to test for differences among three or more groups. If you are only testing for a difference between two groups, use a t-test instead.
Multiple linear regression is a regression model that estimates the relationship between a quantitative dependent variable and two or more independent variables using a straight line.
Linear regression most often uses mean-square error (MSE) to calculate the error of the model. MSE is calculated by:
Linear regression fits a line to the data by finding the regression coefficient that results in the smallest MSE.
Simple linear regression is a regression model that estimates the relationship between one independent variable and one dependent variable using a straight line. Both variables should be quantitative.
For example, the relationship between temperature and the expansion of mercury in a thermometer can be modeled using a straight line: as temperature increases, the mercury expands. This linear relationship is so certain that we can use mercury thermometers to measure temperature.
A regression model is a statistical model that estimates the relationship between one dependent variable and one or more independent variables using a line (or a plane in the case of two or more independent variables).
A regression model can be used when the dependent variable is quantitative, except in the case of logistic regression, where the dependent variable is binary.
The literature review usually comes near the beginning of your thesis or dissertation. After the introduction, it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology.
There are several reasons to conduct a literature review at the beginning of a research project:
Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.
A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question.
It is often written as part of a thesis, dissertation, or research paper, in order to situate your work in relation to existing knowledge.
The sections in your graduate school resume depend on two things: your experience, and the focus of the program you’re applying to.
Always start with your education. If you have more than one degree, list the most recent one first.
The title and order of the other sections depend on what you want to emphasize. You might include things like:
The resume should aim for a balance between two things: giving a snapshot of what you’ve done with your life so far, and showing that you’re a good candidate for graduate study.
A resume is typically shorter than a CV, giving only the most relevant professional and educational highlights.
An academic CV should give full details of your education and career, including lists of publications and presentations, certifications, memberships, grants, and research projects. Because it is more comprehensive, it’s acceptable for an academic CV to be many pages long.
Note that, outside of the US, resume and CV are often used interchangeably.
No, don’t include your high school courses and grades. The education section should only detail your college education.
If you want to discuss aspects of high school in your graduate school application, you can include this in your personal statement.
A resume for a graduate school application is typically no more than 1–2 pages long.
Note, however, that if you are asked to submit a CV (curriculum vitae), you should give comprehensive details of all your academic experience. An academic CV can be much longer than a normal resume.
Always carefully check the instructions and adhere to any length requirements for each application.
A t-test should not be used to measure differences among more than two groups, because the error structure for a t-test will underestimate the actual error when many groups are being compared.
If you want to compare the means of several groups at once, it’s best to use another statistical test such as ANOVA or a post-hoc test.
A one-sample t-test is used to compare a single population to a standard value (for example, to determine whether the average lifespan of a specific town is different from the country average).
A paired t-test is used to compare a single population before and after some experimental intervention or at two different points in time (for example, measuring student performance on a test before and after being taught the material).
A t-test measures the difference in group means divided by the pooled standard error of the two group means.
In this way, it calculates a number (the t-value) illustrating the magnitude of the difference between the two group means being compared, and estimates the likelihood that this difference exists purely by chance (p-value).
Your choice of t-test depends on whether you are studying one group or two groups, and whether you care about the direction of the difference in group means.
If you are studying one group, use a paired t-test to compare the group mean over time or after an intervention, or use a one-sample t-test to compare the group mean to a standard value. If you are studying two groups, use a two-sample t-test.
If you want to know only whether a difference exists, use a two-tailed test. If you want to know if one group mean is greater or less than the other, use a left-tailed or right-tailed one-tailed test.
A t-test is a statistical test that compares the means of two samples. It is used in hypothesis testing, with a null hypothesis that the difference in group means is zero and an alternate hypothesis that the difference in group means is different from zero.
MLA Style is the second most used citation style (after APA). It is mainly used by students and researchers in humanities fields such as literature, languages, and philosophy.
If information about your source is not available, you can either leave it out of the MLA citation or replace it with something else, depending on the type of information.
A standard MLA Works Cited entry is structured as follows:
Only include information that is available for and relevant to your source.
In mixed methods research, you use both qualitative and quantitative data collection and analysis methods to answer your research question.
The research methods you use depend on the type of data you need to answer your research question.
Statistical significance is a term used by researchers to state that it is unlikely their observations could have occurred under the null hypothesis of a statistical test. Significance is usually denoted by a p-value, or probability value.
Statistical significance is arbitrary – it depends on the threshold, or alpha value, chosen by the researcher. The most common threshold is p < 0.05, which means that the data is likely to occur less than 5% of the time under the null hypothesis.
When the p-value falls below the chosen alpha value, then we say the result of the test is statistically significant.
A test statistic is a number calculated by a statistical test. It describes how far your observed data is from the null hypothesis of no relationship between variables or no difference among sample groups.
The test statistic tells you how different two or more groups are from the overall population mean, or how different a linear slope is from the slope predicted by a null hypothesis. Different test statistics are used in different statistical tests.
Statistical tests commonly assume that:
If your data does not meet these assumptions you might still be able to use a nonparametric statistical test, which have fewer requirements but also make weaker inferences.
Avoid citing sources in your abstract. There are two reasons for this:
There are some circumstances where you might need to mention other sources in an abstract: for example, if your research responds directly to another study or focuses on the work of a single theorist. In general, though, don’t include citations unless absolutely necessary.
An abstract is a concise summary of an academic text (such as a journal article or dissertation). It serves two main purposes:
Abstracts are often indexed along with keywords on academic databases, so they make your work more easily findable. Since the abstract is the first thing any reader sees, it’s important that it clearly and accurately summarizes the contents of your paper.
In an APA Style paper, the abstract is placed on a separate page after the title page (page 2).
An APA abstract is around 150–250 words long. However, always check your target journal’s guidelines and don’t exceed the specified word count.
Yes. MLA style uses title case, which means that all principal words (nouns, pronouns, verbs, adjectives, adverbs, and some conjunctions) are capitalized.
This applies to titles of sources as well as the title of, and subheadings in, your paper. Use MLA capitalization style even when the original source title uses different capitalization.
The title of an article is not italicized in MLA style, but placed in quotation marks. This applies to articles from journals, newspapers, websites, or any other publication. Use italics for the title of the source where the article was published. For example:
Use the same formatting in the Works Cited entry and when referring to the article in the text itself.
In MLA style, book titles appear in italics, with all major words capitalized. If there is a subtitle, separate it from the main title with a colon and a space (even if no colon appears in the source). For example:
The format is the same in the Works Cited list and in the text itself. However, when you mention the book title in the text, you don’t have to include the subtitle.
The title of a part of a book—such as a chapter, or a short story or poem in a collection—is not italicized, but instead placed in quotation marks.
The DOI is usually clearly visible when you open a journal article on an academic database. It is often listed near the publication date, and includes “doi.org” or “DOI:”. If the database has a “cite this article” button, this should also produce a citation with the DOI included.
If you can’t find the DOI, you can search on Crossref using information like the author, the article title, and the journal name.
In MLA style citations, format a DOI as a link, including “https://doi.org/” at the start and then the unique numerical code of the article.
DOIs are used mainly when citing journal articles in MLA.
A DOI is a unique identifier for a digital document. DOIs are important in academic citation because they are more permanent than URLs, ensuring that your reader can reliably locate the source.
Journal articles and ebooks can often be found on multiple different websites and databases. The URL of the page where an article is hosted can be changed or removed over time, but a DOI is linked to the specific document and never changes.
A confounding variable, also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.
A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.
In your research design, it’s important to identify potential confounding variables and plan how you will reduce their impact.
Discrete and continuous variables are two types of quantitative variables:
Quantitative variables are any variables where the data represent amounts (e.g. height, weight, or age).
Categorical variables are any variables where the data represent groups. This includes rankings (e.g. finishing places in a race), classifications (e.g. brands of cereal), and binary outcomes (e.g. coin flips).
You need to know what type of variables you are working with to choose the right statistical test for your data and interpret your results.
You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause, while a dependent variable is the effect.
In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable. For example, in an experiment about the effect of nutrients on crop growth:
Defining your variables, and deciding how you will manipulate and measure them, is an important part of experimental design.
The MLA Handbook is currently in its 9th edition, published in 2021.
This quick guide to MLA style explains the latest guidelines for citing sources and formatting papers according to MLA.
The fastest and most accurate way to create MLA citations is by using Scribbr’s MLA Citation Generator.
Search by book title, page URL or journal DOI to automatically generate flawless citations, or cite manually using the simple citation forms.
MLA recommends using 12-point Times New Roman, since it’s easy to read and installed on every computer. Other standard fonts such as Arial or Georgia are also acceptable. If in doubt, check with your supervisor which font you should be using.
Experimental design means planning a set of procedures to investigate a relationship between variables. To design a controlled experiment, you need:
When designing the experiment, you decide:
Experimental design is essential to the internal and external validity of your experiment.
Internal validity is the degree of confidence that the causal relationship you are testing is not influenced by other factors or variables.
External validity is the extent to which your results can be generalized to other contexts.
The validity of your experiment depends on your experimental design.
In APA Style, all sources that are not retrievable for the reader are cited as personal communications. In other words, if your source is private or inaccessible to the audience of your paper, it’s a personal communication.
Common examples include conversations, emails, messages, letters, and unrecorded interviews or performances.
Interviews you conducted yourself are not included in your reference list, but instead cited in the text as personal communications.
Published or recorded interviews are included in the reference list. Cite them in the usual format of the source type (for example, a newspaper article, website or YouTube video).
When you quote or paraphrase a specific passage from a source, you need to indicate the location of the passage in your in-text citation. If there are no page numbers (e.g. when citing a website) but the text is long, you can instead use section headings, paragraph numbers, or a combination of the two:
(Caulfield, 2019, Linking section, para. 1).
Section headings can be shortened if necessary. Kindle location numbers should not be used in ebook citations, as they are unreliable.
If you are referring to the source as a whole, it’s not necessary to include a page number or other marker.
APA Style usually does not require an access date. You never need to include one when citing journal articles, e-books, or other stable online sources.
However, if you are citing a website or online article that’s designed to change over time, it’s a good idea to include an access date. In this case, write it in the following format at the end of the reference: Retrieved October 19, 2020, from https://www.uva.nl/en/about-the-uva/about-the-university/about-the-university.html