How to (1)Comment on the R-squared.

Question

(2). Conduct the test of significance for the regression equation in part 1. Interpret your finding.
(3). Interpret the correlation coefficient.
(4). Test the significance of the strength of relationship. ( use á =.10)

Data
School-Enroll-Per Faculty-Tuition-Foreign Tuition-Age-%Foreign-Start Salary
A---200--5--24420--29,600--28--47--71400
B---228--4--19993--32,582--29--28--65200
C---392--5--4300--4300--22--0--7100
D---90--5--11140--11140--29--10--31000
E---126--4--33060--33060--28--60--87000

Answer 1

For correlation, r^2 is a measure of effect size. It's the correlation coefficient squared and basically represents the proportion of variability that is shared by two variables. The r^2 value may show this effect to be strong or weak.
As an example, suppose we have r^2 = .44; this means the proportion of variability shared by two variables represents a strong effect.

I hope this will help.