Answer: 59% of the total variation in the dependent variable is explained by the independent variables.

## Explanation The coefficient of determination (R-squared) is a statistical measure that shows the proportion of the variance for a dependent variable that's explained by independent variables in a regression model. **Key Points:** - **R-squared = 0.59** means that **59% of the total variation in the dependent variable** is explained by the independent variables - This indicates how well the independent variables collectively predict the dependent variable - The remaining 41% of variation is unexplained and attributed to other factors **Why other options are incorrect:** - **A**: Incorrect - R-squared measures variation explained by independent variables, not the dependent variable - **B**: Incorrect - Correlation coefficient and R-squared are different measures; correlation coefficient would be √0.59 ≈ 0.768 - **C**: Incorrect - High R-squared doesn't necessarily indicate multicollinearity among independent variables **Interpretation:** In this multiple regression context with three independent variables, an R-squared of 0.59 indicates that the model explains 59% of the variability in the dependent variable, which is a moderately good fit.

Author: Tanishq Prabhu