Final answer:
The statement that R-squared = 1 indicates the regression is a perfect fit of the data is true, as it means all data points fall exactly on the regression line. R-squared values range from 0 to 1 and represent the proportion of variance in the dependent variable predictable from the independent variable(s).
Step-by-step explanation:
When R-squared = 1, it does indeed indicate that the regression is a perfect fit of the data, meaning all the observed data points fall exactly on the regression line. This statement is true. The R-squared value, also known as the coefficient of determination, tells us the proportion of the variance in the dependent variable that is predictable from the independent variable(s).
In the example provided, the coefficient of determination is r² = .4397, which means approximately 44 percent of the variation in final exam grades is explained by the variation in the third exam grades using the best-fit regression line. This indicates a moderate strength of the linear relationship between the variables. It is important to note that R-squared values range from 0 to 1 where a value close to 0 suggests that the model does not explain much of the variability, while a value close to 1 indicates that the model explains much of the variability.