The R-squared of a regression is 1 - X, where X is the:
A) sum of squared residuals divided by the total sum of squares.
B) sum of squared predictions divided by the total sum of squares.
C) sum of squared residuals divided by the sum of squared predictions.
D) sum of squared predictions divided by the sum of squared residuals.

Question

Quizplus · Accepted Answer

The formula for R-squared is 1 - (sum of squared residuals/total sum of squares), where the sum of squared residuals is the sum of the differences between the actual values and predicted values squared, and the total sum of squares is the sum of the differences between the actual values and the mean of the values squared. This value ranges from 0 to 1, with higher values indicating a better fit of the regression line to the data. Therefore, A is the correct choice as it represents the formula for calculating R-squared.

The R-Squared of a Regression Is 1 - X, Where