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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.
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
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.
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