How do you Compute Var(Y) and Cor (Y,X) with the given data?

Yes, SST = SSR + SSE, but be careful to make sure you add correctly, however, SST is a sum of squares, not a variance. You need to do something to it.

As for the correlation ... here's a couple of hints:

- what's the symbol for sample correlation?

- be careful with the sign

===

SST is.not.variance.

Look at the formula for variance (at least google it) See how it is different from SST.

You DO NOT NEED the mean of y.

You need a correlation. You already have a number that is closely related to correlation. Look more closely at R^2. What is it? What does it measure?

SST(corrected)=sum(yi-mean of y)^2

"if I had y-bar and y i would do it this way, "

I know

I was wanting to say that what you have there in table, SST(corrected) is sum(yi-mean of y)^2, which looks like the variance, except you have do do something

you are close to the answer

"The Constant Variable is B0 and the X is B1."

No, the B1 is the coefficient of X(the slope) B0 is the intercept of the linr

So you have the regression equation

Y=B0+B1*X

"I don't see how you are getting a y mean."

I didn't say you are getting a y mean. I didn't say you have to calculate y mean I just explained to you what means that SST. In other words, how was calculated by the program.

efqy said "SST is a sum of squares, not a variance."

Looked in any place(book, internet) where the variance is defined and see it it is only a sum of squares and what is the difference