Description: A dummy variable is a numerical variable used in regression analysis to represent subgroups of the sample. These variables are fundamental in statistics as they allow the inclusion of categorical variables in regression models that would otherwise only accept numerical variables. Dummy variables take values of 0 or 1, where 1 indicates the presence of a specific characteristic and 0 indicates its absence. For example, in a study on the impact of categorical factors on a response variable, a dummy variable could be created to indicate different categories, such as gender in a salary analysis, where 1 might represent one category (e.g., men) and 0 another (e.g., women). This allows analysts to assess how these categories affect the response variable while controlling for other variables. Dummy variables are especially useful in multiple regression models, where the goal is to understand the relationship between multiple independent variables and a dependent variable. Their use facilitates the interpretation of results, as it allows for the breakdown of the effect of different categories within the same analysis. Additionally, their implementation is straightforward and can be performed in most statistical software, making them an accessible tool for researchers and data analysts.
