Question

18. SSE can never be
O larger than SST
smaller than SST
ООО
O equal to 1
O equal to zero​

Answer 1

Answer:

Equal to 1...........

Answer 2

Answer:equal to 1

Explanation:

Sum Squared Error (SSE) is an accuracy degree in which the mistakes are squared, then added. It is used to decide the accuracy of the forecasting version whilst the information factors are comparable in magnitude. The decrease the SSE the greater correct the forecast.Sum of squared mistakes (SSE) is in reality the weighted sum of squared mistakes if the heteroscedastic mistakes choice isn't same to regular variance. The suggest squared error (MSE) is the SSE divided through the stages of freedom for the mistakes for the restrained version, that is n-2(k+1).

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