A realtor used the regression model, y = beta0 + beta1x1 +beta2x2 + epsilon, to
ID: 3228890 • Letter: A
Question
A realtor used the regression model, y = beta0 + beta1x1 +beta2x2 + epsilon, to predict selling prices of homes (in thousands of $) in a Columbus suburb. The variable x1 represents the home size (square feet), and x2 represents the number of bedrooms. The following Excel partial output is available. ANOVA df SS MS F Regression 2 5800.44 2900.22 92.66 Residual 10 312.99 31.30 Total 12 6113.43 Coefficients Standard Error t Stat Intercept 27.13 22.80 1.19 Size 0.16 0.03 5.33 Bedrooms 20.22 6.42 3.15 What is the estimated variance of the error term epsilon?
Explanation / Answer
estimated variance of the error term epsilon is the variance of residual term
2 = SSE / (n - number of parameters in model) = MSE = 31.30
so estimated variance of error term epsilon = 31.30