SEE vs SSE

CFA Level II
#1

Is there a mathematical link between the standard error of estimate and the sum of square error?

#2

SEE=square root of (SSE/n-2)

#3

Thanks!

So Sum (y - y’)^2 = Sum (Yi - b0 - b1Xi)^2 ?

#4

Correct. You should note that the degrees of freedom isn’t always (n-2). If you have more independent variables and still fit an intercept, the DF are (n-k-1); n=sample size, k=estimated parameters aside from the intercept, 1 for the intercept.

#5

Keep in mind the various terms that can be used to refer to SSE and SEE. This is what is the most confusing part about the whole thing.