![]() ![]() ![]() First, we introduce the example that is used in this guide. ![]() In the section, Procedure, we illustrate the SPSS Statistics procedure to perform a chi-square test for independence. Example independent variables that meet this criterion include gender (2 groups: Males and Females), ethnicity (e.g., 3 groups: Caucasian, African American and Hispanic), physical activity level (e.g., 4 groups: sedentary, low, moderate and high), profession (e.g., 5 groups: surgeon, doctor, nurse, dentist, therapist), and so forth. Assumption #2: Your two variable should consist of two or more categorical, independent groups.You can learn more about ordinal and nominal variables in our article: Types of Variable. Assumption #1: Your two variables should be measured at an ordinal or nominal level (i.e., categorical data).If it does not, you cannot use a chi-square test for independence. You need to do this because it is only appropriate to use a chi-square test for independence if your data passes these two assumptions. When you choose to analyse your data using a chi-square test for independence, you need to make sure that the data you want to analyse "passes" two assumptions. The chi-square test for independence, also called Pearson's chi-square test or the chi-square test of association, is used to discover if there is a relationship between two categorical variables. Chi-Square Test for Association using SPSS Statistics Introduction
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