Let's assume a linear prediction model E( y) =a + bx. And think about a correlation measure, 'r' (=Pearson correlation measure) on it (i.e., between x and y). How is 'r' related to the slope of the model, 'b'? Does 'b' value directly tell you the strengh of the association? 2) In ANOVA (=analysis of variability) table, you are typically seeing sum of squares (i.e., regression(model) SS, residual SS, and total SS) What is residual SS (=SSE)? And how is it related to the size of R-square