Consider the following ANOVA table for a multiple regression model relating housing prices (in thousands of dollars) to the number of bedrooms in the house and the size of the lot on which the house was built (in square feet). There were 87 total observations. Estimated Price = 21,763.23 + 2967.68 (Bedrooms) +0.2003 (Lot Size) df SS Regression 2 343,952.4330 Residual 84 631,304.4390 Total 86 975,256.8720 ANOVA MS 171,976.2165 7515.5290 F Significance F 22.8828 1.1669E-08 What percent of variation in housing prices is explained by the number of bedrooms and lot size? Round your answer to two decimal places.

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14.2
Consider the following ANOVA table for a multiple regression model relating housing prices (in thousands of dollars) to the number of bedrooms in the house and the
size of the lot on which the house was built (in square feet). There were
87 total observations.
Estimated Price = 21,763.23 +2967.68 (Bedrooms) + 0.2003 (Lot Size
ANOVA
df
SS
MS
F
Significance F
Regression 2 343,952.4330 171,976.2165 22.8828 1.1669E-08
7515.5290
Residual 84 631,304.4390
Total
86
975,256.8720
What percent of variation in housing prices is explained by the number of bedrooms and lot size? Round your answer to two decimal places.
Transcribed Image Text:Consider the following ANOVA table for a multiple regression model relating housing prices (in thousands of dollars) to the number of bedrooms in the house and the size of the lot on which the house was built (in square feet). There were 87 total observations. Estimated Price = 21,763.23 +2967.68 (Bedrooms) + 0.2003 (Lot Size ANOVA df SS MS F Significance F Regression 2 343,952.4330 171,976.2165 22.8828 1.1669E-08 7515.5290 Residual 84 631,304.4390 Total 86 975,256.8720 What percent of variation in housing prices is explained by the number of bedrooms and lot size? Round your answer to two decimal places.
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