The standard error of the regression (SER) is defined as follows
A) $\frac { 1 } { n - 2 } \sum _ { i = 1 } ^ { n } \hat { u } _ { i } ^ { 2 }$
B) S S R
C) $1 - R ^ { 2 }$
D) $\frac { 1 } { n - 1 } \sum _ { i = 1 } ^ { n } \hat { u } _ { i } ^ { 2 }$

Question

The standard error of the regression (SER) is defined as follows
A) $\frac { 1 } { n - 2 } \sum _ { i = 1 } ^ { n } \hat { u } _ { i } ^ { 2 }$
B)  S S R 
C) $1 - R ^ { 2 }$
D) $\frac { 1 } { n - 1 } \sum _ { i = 1 } ^ { n } \hat { u } _ { i } ^ { 2 }$

Quizplus · Accepted Answer

The standard error of the regression (SER) is calculated as the square root of the sum of squared residuals divided by the degrees of freedom, which is $n - 2$ for a simple linear regression.

The Standard Error of the Regression (SER) Is Defined as Follows