In linear regression, which variable is typically considered the independent variable?

In linear regression, the independent variable is the one that is used to predict or explain changes in the dependent variable. Typically, the X variable is designated as the independent variable, as it is the predictor in the equation. In contrast, the Y variable represents the dependent variable, which is the outcome being predicted based on the values of the X variable. Therefore, identifying the X variable as the independent variable aligns with the fundamental principles of linear regression, where the aim is to understand how variations in the X variable influence or determine changes in the Y variable.

The other choices do not represent the independent variable in this context, reinforcing the correctness of designating the X variable for this role.