What type of variable can be represented with a binary value in regression analysis?

In regression analysis, a binary variable, also known as a dummy variable, is used to represent categorical data that can take on two possible values, typically coded as 0 and 1. This type of variable allows researchers to incorporate categorical information into regression models, thereby enabling the analysis of its impact on the dependent variable.

For instance, if you want to examine the effect of gender on salary, you could create a dummy variable where male is represented as 1 and female as 0. This binary coding allows the regression model to quantify the difference in salaries between the two groups while maintaining the integrity and interpretability of the regression equations.

The other types of variables mentioned, such as numeric, continuous, and ordinal, do not specifically refer to the binary representation. Numeric and continuous variables can take on a wide range of values, while ordinal variables involve categories with a specific order, but they don’t have the binary distinction necessary for coding as a dummy variable in regression analysis.