Step 1: Understanding the Concept:
In regression analysis, the relationship between variables is modeled using independent and dependent variables.
Step 2: Detailed Explanation:
In a simple linear regression model:
\[ Y = \beta_0 + \beta_1 X + \epsilon \]
The variable $X$ is the input or explanatory variable, which is manipulated or observed to explain variation in $Y$.
This independent variable ($X$) is commonly referred to as the Regressor, predictor, or explanatory variable.
The variable $Y$ is the output or outcome variable, whose variation we want to explain.
This dependent variable ($Y$) is commonly referred to as the Regressand, predictand, or response variable.
Therefore, the independent variable is synonymous with the term Regressor.
Step 3: Final Answer:
The independent variable is also called the Regressor.