Dummy variables, sometimes referred to as indicator variables, are a common data preparation step to represent categorical (or qualitative) variables as a series of dichotomous (i.e., 0/1) variables. This technique is useful to recreate an analysis of variance model in a regression framework, which is achieved by creating c − 1 new dichotomous variables from a categorical variable, where c represents the number of groups, categories, or levels of the original categorical variable. For example, a variable representing a high school graduated student (i.e., graduated vs. did not graduate) was created by assigning a value of 1 if the student graduated from high school or 0 otherwise. This entry explores in more detail the creation, interpretation, and reasons for using dummy variables.
Creating dummy ...
Looks like you do not have access to this content.