A realtor used the regression model, y betao +beta1x1 +beta2x2+ epsilon, to pred

Question

A realtor used the regression model, y betao +beta1x1 +beta2x2+ epsilon, to predict selling prices of homes (in thousands of $) in a Columbus suburb The variablex1 represents the home size (square feet), and x2 represents the number of bedrooms. The following Excel partial output is available ANOVA df Regression 2 Residual 10 12 5800.44 312.99 6113.43 MS 2900.22 92.66 31.30 Total Coefficients Standard Intercept 27.13 Size Bedrooms 20.22 Error 22.80 0.03 6.42 1.19 5.33 3.15 0.16 What is the estimated variance of the error term epsilon?

Explanation / Answer

here as we know that estimated varaince of error term epsilon =mean square (residaul)=31.30

( please revert if there are other parts of this)

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