Simple Questions

#1
...and yet i'm stuck.

1) How would you represent the components of ANOVA of regression in a graphic format,when considering a bivariate regression? How would you do describe these components for two predictors?

Basically in the context of the ANOVA table wrt to Regression:
SSTotal = total variation of Y scores around the mean of Y
SSRegression = represents the sum of squared distance between the predicted scores of Y by the regression line Yhat and the grand mean of Y
SSerror = represents the total variation of points and the corresponding points on the regression line.

I'm having some trouble translating this into the multiple regression case with 2 predictors

2)When is it appropriate to perform a transformation? What is the justification for performing a transformation? (In other words, why is it okay to perform a transformationon data?). What is the connection between the transformed sample, the sampling distribution and the population distribution?

A transformation is appropriate if your original scores do not conform to assumptions of the test you plan to use (i.e, normality, homogeneity of variances).

Please help with the rest of this question.!

TIA