The MSE for the given situation is 14.8 if SSE for variance problem is 399.6
In insights, the mean squared error (MSE) or mean squared deviation (MSD) of an assessor (of a system for assessing an unseen amount) gauges the normal of the squares of the mistakes — that is, the typical squared contrast between the assessed values and the real worth. MSE is a gamble capability, relating to the normal worth of the squared mistake misfortune
We know very well that MSE=SSE / r×(c-1)
where r is defined as the number of treatments
and c is defined as the total number of treatments
MSE=Variance within the sample
SSE=Sum of squares of the error
We have values of SSE=399.6,r=3 and value of c=10.
According to the question, so on putting the values, we get
=>MSE=399.6/3(10-1)
=>MSE=399.6/(3×9)
=>MSE=399.6/27
=>MSE=14.8
Hence, the MSE for the analysis would be 14.8
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