Step 1

Chi-square tests are nonparametric tests that examine nominal categories as opposed to numerical values.

Step 2

In ANOVA, we have two or more group means that we have to compare. In Chi square test, we have two categorical variables and want to determine whether one variable is related to the other variable.

Suppose, we had conducted an ANOVA, with individuals grouped by political affiliation(Republican, Democrat and other) and we were interested in how satisfied they were with the current administration. Satisfaction was measured on a scale of1-10, so it was measured on a continuous scale.

For instance, rather than looking at test scores as a range from 0 to 10, you could change the variable to low, medium or high. so that it becomes categorical, thus amenable for Chi square test.

Here, non parametric test is the better option for this hypothesis since data are not given as normally distributed and the non-parametric test which is distribution free is applicable here.

Chi-square tests are nonparametric tests that examine nominal categories as opposed to numerical values.

Step 2

In ANOVA, we have two or more group means that we have to compare. In Chi square test, we have two categorical variables and want to determine whether one variable is related to the other variable.

Suppose, we had conducted an ANOVA, with individuals grouped by political affiliation(Republican, Democrat and other) and we were interested in how satisfied they were with the current administration. Satisfaction was measured on a scale of1-10, so it was measured on a continuous scale.

For instance, rather than looking at test scores as a range from 0 to 10, you could change the variable to low, medium or high. so that it becomes categorical, thus amenable for Chi square test.

Here, non parametric test is the better option for this hypothesis since data are not given as normally distributed and the non-parametric test which is distribution free is applicable here.