Hey guys!

I have a silly question regarding “Multiple R” (and I didn’t find the answer in the forum). Multiple R is defined as the correlation between predicted and actual values of the dependent variable. Why the values of the IV are called “predicted values” and the values of the DV the “actual values”?

Also, it is ok to assume that in simple linear regression (with 1 IV), the “r” can be between -1 and 1 but the Multiple R can go between 0 and 1? Why is that? How we can calculate Multiple R?

Thanks in advance!

They’re not saying that the values of the independent variables are the predicted values. They’re saying that the values that you get from the regression formula are the predicted values: the _ŷ_s.

Multiple R is the square root of R^{2}. So, for a simple regression, it’s the absolute value of the correlation coefficient.

Perfect!

Ok, so it’s the absolute value, but we would consider the sign for a single linear regression (1 IV).

I haven’t finished the reading, but is there a way to calculate Multiple R besides taking the square root or is out of the scope of the reading?

Thank you Bill!

You might be able to compute Multiple R as the correlation of the actual *y*-values and the predicted *y*-values, but I’m not sure about that. I’ll have to give it a whirl.

tickersu would know off the top of his head.