SSE can never be?
Understand the Problem
The question is asking about the relationships between the Sum of Squares Error (SSE) and the Total Sum of Squares (SST) in the context of statistics. It is seeking to clarify whether SSE can be larger, smaller, equal to one, or equal to zero in relation to SST.
Answer
SSE can never be larger than SST.
The final answer is larger than SST.
Answer for screen readers
The final answer is larger than SST.
More Information
In regression analysis, the total variability (SST) is partitioned into the variability explained by the model (SSR) and the unexplained variability (SSE). Since SST = SSR + SSE, SSE can never exceed SST.
Tips
A common mistake is confusing SSE with SSR or not realizing the relationship between SST, SSR, and SSE in the equation SST = SSR + SSE.
Sources
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