What is the partitioning of a regression?
Regression partitions are: the sum of squares predicted and the sum of squares error.
Regression can divide the variation in Y (the dependent Variable) into two parts: the variation of the predicted scores and the variation of the errors of prediction. The variation of Y is called the sum of squares Y and is defined as the sum of the squared deviations of Y from the mean of Y. In the population, the formula is
where SSY is the sum of squares Y, Y is an individual value of Y, and