Question

× 215-QL Q Microsoft Word-QM215 Quiz t 4: SU2018 Q 0M2 15%20Quiz%204.pdf QM215 Quiz 4 Use the following output for Questions 1-5 A realtor built a regression model to explain the selling price of homes in a large Midwestern city. The variables are: PRICE -The sales price is measured in thousands of dollars. For example, a value of home that sold for $269,000 will have a value of 269 in this dataset. SQFT- The size of the living area in the house measured in thousands of square feet. For example, a home with 2,250 square feet will have a value of 2.25 in the dataset BATH- The number of bathrooms. ACREAGE- The size of the lots measured in acres. The regression output is shown below: Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.919 0.844 0.834 32.5 Question 1 ANOVA MS Regression Residual Total 3262252.2 874174 82.901.42053-18 46 Question 2 49 310756.8 1054.4 Standaro Error Upper 95% Coefficients 11.37 44.58 24.34 25.65 tStat p.volue Lower 95% Intercept sqft bath 16.30 0.70 0.4887 6.19 7.20 0.0000 8.40 2.90 0.0057 41 7.52 0.0000 1.4344.17 32.1257.05 41.25 32.52 Lower 95.0% -21.43 32.12 7.43 18.78 7.43 18.78 TO

Need help with 1-5

Answer 1

1)

df_total = n-1 = 49
n = 50

2)
Residual SS = SS total - SS regression
= 310756.8-262252.2
=48504.6

3)
estimated coefficient for the number of baths = 24.34 {see the column coefficent and row bath}

4)
this is given by 100* R^2
= 100 * 0.844
=84.4 %