For the following data, the value of SSE = 18. $$\begin{array} { l l }
\text { Dependent Variable } ( y ) & \text { Independent Variable } ( x ) \
15 & 4 \
17 & 6 \
23 & 2 \
17 & 4
\end{array}$$ The total sum of squares (SST) equals
A) 36.
B) 18.
C) 9.
D) 2.

Question

For the following data, the value of SSE = 18. $$\begin{array} { l l } 
\text { Dependent Variable } ( y ) & \text { Independent Variable } ( x ) \
15 & 4 \
17 & 6 \
23 & 2 \
17 & 4
\end{array}$$   The total sum of squares (SST) equals
A) 36.
B) 18.
C) 9.
D) 2.

Quizplus · Accepted Answer

The total sum of squares (SST) is the sum of the squared differences between each observed value and the mean of the observed values. SSE is the sum of squared errors, which is part of the decomposition of SST. Given SSE = 18, and knowing that SST = SSR + SSE, where SSR is the regression sum of squares, SST must be greater than or equal to SSE. The only option greater than 18 is 36.