SSE can never be
A)larger than SST
B)smaller than SST
C)equal to 1
D)equal to zero

Question

Quizplus · Accepted Answer

SSE (sum of squared errors) represents the variation that is not explained by the regression model, while SST (total sum of squares) represents the total variation in the data. As SSE only captures a subset of the total variation in the data, it can never be larger than SST. Thus, option A is the best choice. Option B is incorrect as SSE can be smaller or equal to SST. Option C is incorrect as SSE can take any value greater than or equal to zero. Option D is incorrect because if SSE is equal to zero, it implies that the regression model perfectly fits the data, which is possible.

SSE Can Never Be