Answer: of either 0 or 1.

## Explanation An indicator variable (also known as a dummy variable or binary variable) in simple linear regression is a categorical variable that takes only two values: 0 or 1. **Key Points:** 1. **Definition**: Indicator variables are used to represent categorical data in regression models. They take the value 1 when a certain condition is true and 0 when it is false. 2. **Purpose**: They allow the inclusion of qualitative variables (like gender, yes/no responses, presence/absence) in regression analysis. 3. **Why not the other options:** - **Option B (between 0 and 1)**: This describes continuous variables that can take any value between 0 and 1, not indicator variables. - **Option C (in the range -1 to 1)**: This describes correlation coefficients or standardized variables, not indicator variables. 4. **Example**: In a regression model predicting salary, an indicator variable for gender might be coded as: - 1 for male - 0 for female 5. **Interpretation**: The coefficient of an indicator variable represents the average difference in the dependent variable between the group coded as 1 and the reference group coded as 0. **Correct Answer**: A - Indicator variables take values of either 0 or 1.

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