NBA Player Salary Determinants: Analyzing Experience, Points, and R-squared

The R2 is a statistical measure that represents the proportion of the variance in the dependent variable (Wage) that can be explained by the independent variables (Exper and Points) in the regression model.

In equation (2), the R2 value of 0.470 means that approximately 47% of the variation in players' salaries can be explained by their NBA experience and the number of points they score per game. This indicates that these two variables have a moderate level of predictive power in determining players' salaries.

In equation (3), the R2 value of 0.483 means that approximately 48.3% of the variation in players' salaries can be explained by their NBA experience, squared NBA experience, and the number of points they score per game. This indicates that adding the squared NBA experience variable improves the model's ability to predict players' salaries slightly compared to equation (2).

The R2 is higher for equation (3) than for equation (2) because the inclusion of the squared NBA experience variable captures additional nonlinear relationships between NBA experience and salary. This suggests that the relationship between NBA experience and salary is not simply linear but may have a curved or quadratic shape. By including the squared NBA experience variable, equation (3) can better capture this nonlinearity, resulting in a slightly higher R2 value.