1 Compute SX; SXY ; and SY .
> # Put your R code here.

2 Compute the sample correlation matrix (q_p) between the X and Y variables. Test individual
correlations for significance. Discuss your results.
> # Put your R code here.

3 Compute the multiple correlation between each Y variable and the X variables. Test for
significance. What do you conclude?
> # Put your R code here.

4 Compute the partial regression coefficients, i.e., partial correlations, between each Y variable and each X variable adjusting for the other X variables. Test the significance of each. What do you conclude? How do you conclusions differ from those in quesiton 2?
> # Put your R code here.

5 Compute the canonical correlations between the X variables and the Y variables. Sequentially test the canonical correlations for significance. What do you conclude?
> # Put your R code here.

6 Compute the canonical variable scores based on the centered data matrices.

> # Put your R code here.

7 Plot the canonical variables, i.e., Ui versus Vi, corresponding to the significant canonical correlations. Comment on the canonical relationships.
> # Put your R code here.

8 Approximate SXY by a biplot. Discuss the relationships between the X and Y variables in terms of this biplot.
> # Put your R code here.