## What Is Kurtosis? | Definition, Examples & Formula

Kurtosis is a measure of the tailedness of a distribution. Tailedness is how often outliers occur. Excess kurtosis is the tailedness of a distribution relative to a normal distribution.

• Distributions with medium kurtosis (medium tails) are mesokurtic.
• Distributions with low kurtosis (thin tails) are platykurtic.
• Distributions with high kurtosis (fat tails) are leptokurtic.

Tails are the tapering ends on either side of a distribution. They represent the probability or frequency of values that are extremely high or low compared to the mean. In other words, tails represent how often outliers occur.

Example: Types of kurtosis Continue reading: What Is Kurtosis? | Definition, Examples & Formula

## Systematic Review | Definition, Example & Guide

A systematic review is a type of review that uses repeatable methods to find, select, and synthesize all available evidence. It answers a clearly formulated research question and explicitly states the methods used to arrive at the answer.

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## Probability Distribution | Formula, Types, & Examples

A probability distribution is a mathematical function that describes the probability of different possible values of a variable. Probability distributions are often depicted using graphs or probability tables.

Common probability distributions include the binomial distribution, Poisson distribution, and uniform distribution. Certain types of probability distributions are used in hypothesis testing, including the standard normal distribution, Student’s t distribution, and the F distribution.

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## Frequency Distribution | Tables, Types & Examples

A frequency distribution describes the number of observations for each possible value of a variable. Frequency distributions are depicted using graphs and frequency tables.

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The chi-square (Χ2) distribution table is a reference table that lists chi-square critical values. A chi-square critical value is a threshold for statistical significance for certain hypothesis tests and defines confidence intervals for certain parameters.

Chi-square critical values are calculated from chi-square distributions. They’re difficult to calculate by hand, which is why most people use a reference table or statistical software instead.

## Chi-Square Test of Independence | Formula, Guide & Examples

A chi-square (Χ2) test of independence is a nonparametric hypothesis test. You can use it to test whether two categorical variables are related to each other.

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## Chi-Square Goodness of Fit Test | Formula, Guide & Examples

A chi-square (Χ2) goodness of fit test is a type of Pearson’s chi-square test. You can use it to test whether the observed distribution of a categorical variable differs from your expectations.

The chi-square goodness of fit test tells you how well a statistical model fits a set of observations. It’s often used to analyze genetic crosses.

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## Chi-Square (Χ²) Tests | Types, Formula & Examples

A Pearson’s chi-square test is a statistical test for categorical data. It is used to determine whether your data are significantly different from what you expected. There are two types of Pearson’s chi-square tests:

Chi-square is often written as Χ2 and is pronounced “kai-square” (rhymes with “eye-square”). It is also called chi-squared.

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## Chi-Square (Χ²) Distributions | Definition & Examples

A chi-square (Χ2) distribution is a continuous probability distribution that is used in many hypothesis tests.

The shape of a chi-square distribution is determined by the parameter k. The graph below shows examples of chi-square distributions with different values of k. Continue reading: Chi-Square (Χ²) Distributions | Definition & Examples

## Quartiles & Quantiles | Definition, Calculation & Interpretation

Quartiles are three values that split sorted data into four parts, each with an equal number of observations. Quartiles are a type of quantile.

• First quartile: Also known as Q1, or the lower quartile. This is the number halfway between the lowest number and the middle number.
• Second quartile: Also known as Q2, or the median. This is the middle number halfway between the lowest number and the highest number.
• Third quartile: Also known as Q3, or the upper quartile. This is the number halfway between the middle number and the highest number. Quartiles can also split probability distributions into four parts, each with an equal probability.

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