How To Do Chi-Square Tests in Excel?

8.7 min read|Last Updated: November 27th, 2023|Categories: excel|
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The Chi-square test, also known as Pearson’s chi-squared test, is a hypothesis test used to draw inferences and test the relationships between one or multiple categories of variables in the form of the goodness of fit, independence, and homogeneity tests. So it’s a type of Excel data analysis and visualization. In this tutorial, we’re going to learn how to perform chi-square tests in Excel. But first, we need to learn about their applications.

Types of Chi-Square Tests

There are three types of chi-square tests:

1- Chi-square goodness of fit test

2- Chi-square test of independence

3- Chi-square test of homogeneity

What is the Chi-Square Goodness of Fit Test?

The Chi-square goodness of fit test, also referred to as Pearson’s goodness of fit test, is used to determine how well your sample data and the conclusions you make from it represent its population. Like any other hypothesis test, the goodness of fit test needs two initial hypotheses and a significance level (Alpha).

Null hypothesis (H0): The sample data is a good fit for our population.

Alternative hypothesis (Ha): The sample data is not a good fit for our population.

Alpha: It is the threshold value in the hypothesis test by which the null hypothesis can be rejected or accepted. A standard value for Alpha is 0.05.

What is the Chi-Square Test of Independence?

The Chi-square test of independence or Pearson test of independence, as the name suggests, is used to determine whether there is a relation between two groups of variables in a single population. In this test, our hypotheses are as follows:

Null hypothesis (H0): The variables in our sample data are independent of each other.

Alternative hypothesis (Ha): The variables in our sample data are related.

What is the Chi-Square Test of Homogeneity?

In the Chi-Square test of homogeneity, we are looking to see if the distribution of a single variable remains the same in multiple populations of interest. So our hypotheses in this test are:

Null hypothesis (H0): the distribution of the variable of interest is the same in all populations.

Alternative hypothesis (Ha): the distribution of the variable of interest is not the same in all populations.

Now that we have learned what each of these tests is used for, we can explain how to perform them in excel.