Q. When should I use a chi-square test?



Chi-square tests are used when you are comparing two categorical variables. You should perform a chi-square test when you are working with counts of records in different groups. This is different from other hypothesis tests (for example, a t-test) where you are comparing a numerical variable across different groups (i.e. across a categorical variable).

For example, if you were trying to compare the average number of minutes that men and women exercise each day, you would use a hypothesis test. You have a categorical variable (gender) with two levels (men and women) and a numerical quantity of interest (minutes exercised per day). But what if you wanted to compare favorite genre of music while exercising between men and women? This would be a situation for a chi-square test. There are two categorical variables, gender and music genre. Gender has two levels (men and women) and suppose genre has 4 levels (country, rap, rock, and hip-hop). Chi-square tests are often represented with contingency tables like the one shown below. Contingency tables show the observed counts for each group.

The table here is called a contingency table and it has four rows each genre of music, and two columns for gender. Each cell represents the number of observations fall within each combination of music genre and gender. For example, in the first cell is a number 2. This means that there are 2 observations where they are both represented as men and as country music.


  • Last Updated Apr 20, 2021
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  • Answered By Dorian Frampton

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