The Chi-Square Test of Independence
When to Use
The chi-square test of independence (sometimes called the chi-square test of association or homogeneity) is appropriate when both variables are assessed on a nominal level of measurement. That is, when both variables are classification variables. Theoretically, either of the variables can have any number of categories, but in practice the number of categories is usually relatively small, perhaps 2 to 10.
The Two-Way Classification Table
The nature of the relationship between two nominal-level variables is easiest to understand using a two-way classification table. This is a table in which the rows represent the categories of one variable, while the columns represent the categories of the second ...
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