Categorical Predictor/Dummy Variables using SPSS

Categorical Predictor/Dummy Variables

Categorical variables are those variables where the values of a particular variable are in the form of discrete categories. For example Job Rank (Junior, Middle, Senior),  Country of Origin (Pakistan, USA, Spain), or Income Level (Low, Middle, High). In order to add a categorical variable as a predictor in the regression analysis, the categories should be converted into a dummy variable. Each category represents a variable.

Dummy variables (also called indicator variables) are categorical variables that have only two values, 0 and 1. For example, if we would like to use Job rank as a categorical predictor variable in our study, we can create two dummy variables i-e Junior and Middle (the third category serves as a reference category). Each of the two categories (Junior and Middle) will have the value 0 and 1. Where 1 would represent that the respondent belongs to the category and 0 denotes otherwise.

The concept of dummy variables and how to use them in SPSS regression is explained in detail in the following video.

Step by Step guide on how to use Categorical Predictor/Dummy Variables in SPSS