3. What is the mean square error (MSE) of the estimated regression equation? ans
ID: 3154610 • Letter: 3
Question
3. What is the mean square error (MSE) of the estimated regression equation?
answers:
1.96
219.6
27.45
5.24
A realtor used the regression model, y = beta0 + beta1x1 +beta2x2 + epsilon, to predict selling prices of homes (in thousands of $) in a region of California. The variable x1 represents the home size (square feet), and x2 represents the number of bedrooms. The following information is available:
NOVA
Source DF SS MS F
Regression 2 6101.6
Error 219.6
Total 10
Coefficient Standard Error t statistic
Intercept 26.28 22.88 1.15
Size 0.12352 0.02435 5.07
Bedrooms 20.183 6.697 3.01
1. What is the predicted selling price of a home with 1700 square feet and 3 bedrooms?
answers:
About 184, 210 dollars
About 410,300 dollars
About 296,813 dollars
About 154,370 dollrs
2. If for a fixed square footage, a house has one extra bedroom, the predicted selling price
answers:
increases by about 20.18 dollars
increases by about 201,830 dollars
remains unchanged
increases by about 20,183 dollars
1.96
219.6
27.45
5.24
Explanation / Answer
1. What is the predicted selling price of a home with 1700 square feet and 3 bedrooms?
Y = 26.28 + 0.1235 Size + 20.18Beedroms
Y = 26.28 + 0.12352*1700 + 20.183*3
Y = 296.813
About 296,813 dollars
2. If for a fixed square footage, a house has one extra bedroom, the predicted selling price
increases by about 20,183 dollars
3. What is the mean square error (MSE) of the estimated regression equation?
MSE = 219.6 / 8 = 27.45
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