The total sum of squares equals the sum of squares of the variation explained by the regression and the sum of squares of the errors.

Question

Quizplus · Accepted Answer

This statement is true. The total sum of squares (TSS) represents the total variation in the response variable, and it can be decomposed into two components: the explained sum of squares (ESS), which represents the variation in the response variable that is explained by the regression model, and the residual sum of squares (RSS), which represents the unexplained variation in the response variable that is attributable to random error. Thus, TSS = ESS + RSS.

The Total Sum of Squares Equals the Sum of Squares