An introduction to research methods
Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design. When planning your methods, there are two key decisions you will make.
First, decide how you will collect data. Your methods depend on what type of data you need to answer your research question:
- Qualitative vs. quantitative: Will your data take the form of words or numbers?
- Primary vs. secondary: Will you collect original data yourself, or will you use data that has already been collected by someone else?
- Descriptive vs. experimental: Will you take measurements of something as it is, or will you perform an experiment?
Second, decide how you will analyze the data.
- For quantitative data, you can use statistical analysis methods to test relationships between variables.
- For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.
Methods for collecting data
Qualitative vs. quantitative data
Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.
For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data.
If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing, collect quantitative data.
You can also take a mixed methods approach, where you use both qualitative and quantitative research methods.
Primary vs. secondary data
Primary data is any original information that you collect for the purposes of answering your research question (e.g. through surveys, observations and experiments). Secondary data is information that has already been collected by other researchers (e.g. in a government census or previous scientific studies).
If you are exploring a novel research question, you’ll probably need to collect primary data. But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.
Descriptive vs. experimental data
In experimental research, you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design.
To conduct an experiment, you need to be able to vary your independent variable, precisely measure your dependent variable, and control for confounding variables. If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.
Examples of data collection methods
|Research method||Primary or secondary?||Qualitative or quantitative?||When to use|
|Experiment||Primary||Quantitative||To test cause-and-effect relationships.|
|Survey||Primary||Quantitative||To understand general characteristics of a population.|
|Interview/focus group||Primary||Qualitative||To gain more in-depth understanding of a topic.|
|Observation||Primary||Either||To understand how something occurs in its natural setting.|
|Literature review||Secondary||Either||To situate your research in an existing body of work, or to evaluate trends within a research topic.|
|Case study||Either||Either||To gain an in-depth understanding of a specific group or context, or when you don’t have the resources for a large study.|
Methods for analyzing data
Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.
Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.
Qualitative analysis methods
Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:
- From open-ended survey and interview questions, literature reviews, case studies, and other sources that use text rather than numbers.
- Using non-probability sampling methods.
Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions.
Quantitative analysis methods
Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).
You can use quantitative analysis to interpret data that was collected either:
- During an experiment.
- Using probability sampling methods.
Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.
Examples of data analysis methods
|Research method||Qualitative or quantitative?||When to use|
|Statistical analysis||Quantitative||To analyze data collected in a statistically valid manner (e.g. from experiments, surveys, and observations).|
|Meta-analysis||Quantitative||To statistically analyze the results of a large collection of studies.|
Can only be applied to studies that collected data in a statistically valid manner.
|Thematic analysis||Qualitative||To analyze data collected from interviews, focus groups or textual sources.|
To understand general themes in the data and how they are communicated.
|Content analysis||Either||To analyze large volumes of textual or visual data collected from surveys, literature reviews, or other sources.|
Can be quantitative (i.e. frequencies of words) or qualitative (i.e. meanings of words).
Frequently asked questions about research methods
- What’s the difference between quantitative and qualitative methods?
- What is mixed-methods research?
- What is sampling?
A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.
In statistics, sampling allows you to test a hypothesis about the characteristics of a population.
- How do I decide which research methods to use?
- If you want to measure something or test a hypothesis, use quantitative methods. If you want to explore ideas, thoughts and meanings, use qualitative methods.
- If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
- If you want to establish cause-and-effect relationships between variables, use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.
- What’s the difference between method and methodology?
Methodology refers to the overarching strategy and rationale of your research project. It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.
In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section.
In a longer or more complex research project, such as a thesis or dissertation, you will probably include a methodology section, where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.