Learning Objectives

1. Compute the sum of squares Y
2. Convert raw scores to deviation scores
3. Compute predicted scores from a regression equation
4. Partition sum of squares Y into sum of squares predicted and sum of squares error
5. Define r² in terms of sum of squares explained and sum of squares Y.