What values must dummy variables take in a regression model?

In a regression model, dummy variables are used to represent categorical data by transforming categories into a numerical format that can be integrated into the model. The appropriate values for these dummy variables are 0 and 1. Specifically, a dummy variable takes the value of 1 to indicate the presence of a particular category and 0 to indicate its absence.

This binary coding allows the regression analysis to assess the impact of categorical variables on the dependent variable. For example, if you are examining the effect of gender on salary, a dummy variable for gender might be coded as 0 for females and 1 for males. This enables the regression to quantify the average difference in salary between genders based on the coding applied.

The other potential options, which suggest values such as 1 and 2, or any continuous values, do not conform to the standard usage of dummy variables and would complicate the regression analysis process, as they would not accurately represent the two distinct groups intended by the dummy variable approach.