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Sagot :
The value of SSE (sum squared error) is 40 in the given analysis of the variance problem if SST = 120 and SSR = 80. Option b is correct.
How to find SSE in an analysis of variance problems with the SST and SSR values?
Here the words SSE means Sum Squared Error, SST means Sum of Squares Total and SSR means Sum of Square Regression.
In the SSE accuracy measure, errors are squared and then added. It is used when the data points are similar in magnitude.
The formula is SST = SSR + SSE ⇒ SSE = SST - SSR
Calculation:
The given values of the analysis of the variance problem are
SST = 120; SSR = 80
Then, the value of SSE = SST - SSR = 120 - 80 = 40
So, option b is correct.
Learn more about the sum squared error here:
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