If for a fixed square footage, a house has one extra bedroom, the predicted sell

Question

If for a fixed square footage, a house has one extra bedroom, the predicted selling price

What is the estimated variance of the error term epsilon?   

If you conduct a test for the overall significance of the model at a 1% significance level, the critical value for this test is

If you conduct a test for the overall significance of the model, then the p-value of the test is

If you conduct the t test for the significance of Bedrooms, the p-value of the test is

What is the 99% confidence interval for the coefficient beta1 ?

Which of the two independent variables seems to have a stronger impact on the selling price?

      

A realtor used the regression model, y betao + beta1x1 +beta2x2 + epsilon, to predict selling prices of homes (in thousands of S) 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 Regression 2 Residua 10 12 5800.44 312.99 6113.43 MS 2900.22 92.66 31.30 Total Intercept 27.13 Size Bedrooms 20.22 Coefficients Standard Error tStat 1.19 5.33 3.15 22.80 0.03 6.42 0.16

Explanation / Answer

a) If for a fixed square footage, a house has one extra bedroom, the predicted selling price?

predicted selling price increase by 20.22

b) What is the estimated variance of the error term epsilon?

variance of the error term=312.99

c) If you conduct a test for the overall significance of the model at a 1% significance level, the critical value for this test is?

Critical F(2,10)=7.56

d) If you conduct a test for the overall significance of the model, then the p-value of the test is?

P=0.0000

e) What is the 99% confidence interval for the coefficient beta1 ?

Critical t value for 99% at 10 Df, t=3.17

Lower limit = 0.16-3.17*0.03 = 0.0649

upper limit = 0.16+3.17*0.03 = 0.2551

f) Which of the two independent variables seems to have a stronger impact on the selling price?

Size ( t vale for size is larger).

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