Data were collected from a random sample of 330 home sales from a community in 2003. Let Price denote the selling price (in $1,000), BDR denote the number of bedrooms, Bath denote the number of bathrooms, Hsize denote the size of the house (in square feet), Lsize denote the lot size (in square feet), Age denote the age of the house (in years), and Poor denote a binary variable that is equal to 1 if the condition of the house is reported as "poor." An estimated regression yields Price 129.9+0.529BDR+25.5Bath +0.170Hsize +0.004Lsize +0.098Age - 53.2Poor, R2 = 0.78, SER=45.2. her house into a new bathroom. What is the expected increase in the value of the house? Suppose that a homeowner converts part of an existing family room The expected increase in the value of the house is $. (Round your response to the nearest dollar.) Suppose that a homeowner adds a new bathroom to her house, which increases the size of the house by 109 square feet. What is the expected increase in the value of the house? The expected increase in the value of the house is $. (Round your response to the nearest dollar.) What is the loss in value if a homeowner lets his house run down so that its condition becomes "poor"? The loss is $. (Round your response to the nearest dollar.) to the ² for the regression
Data were collected from a random sample of 330 home sales from a community in 2003. Let Price denote the selling price (in $1,000), BDR denote the number of bedrooms, Bath denote the number of bathrooms, Hsize denote the size of the house (in square feet), Lsize denote the lot size (in square feet), Age denote the age of the house (in years), and Poor denote a binary variable that is equal to 1 if the condition of the house is reported as "poor." An estimated regression yields Price 129.9+0.529BDR+25.5Bath +0.170Hsize +0.004Lsize +0.098Age - 53.2Poor, R2 = 0.78, SER=45.2. her house into a new bathroom. What is the expected increase in the value of the house? Suppose that a homeowner converts part of an existing family room The expected increase in the value of the house is $. (Round your response to the nearest dollar.) Suppose that a homeowner adds a new bathroom to her house, which increases the size of the house by 109 square feet. What is the expected increase in the value of the house? The expected increase in the value of the house is $. (Round your response to the nearest dollar.) What is the loss in value if a homeowner lets his house run down so that its condition becomes "poor"? The loss is $. (Round your response to the nearest dollar.) to the ² for the regression
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 26PPS
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Transcribed Image Text:Data were collected from a random sample of 330 home sales from a community in 2003. Let Price denote the selling price (in $1,000), BDR denote the number of bedrooms, Bath denote the number of bathrooms, Hsize
denote the size of the house (in square feet), Lsize denote the lot size (in square feet), Age denote the age of the house (in years), and Poor denote a binary variable that is equal to 1 if the condition of the house is reported as
"poor."
An estimated regression yields
Price=129.9 +0.529BDR+25.5Bath +0.170Hsize +0.004Lsize
+0.098Age-53.2Poor, R² = 0.78, SER=45.2.
Suppose that a homeowner converts part of an existing family room in her house into a new bathroom. What is the expected increase in the value of the house?
The expected increase in the value of the house is $. (Round your response to the nearest dollar.)
Suppose that a homeowner adds a new bathroom to her house, which increases the size of the house by 109 square feet. What is the expected increase in the value of the house?
The expected increase in the value of the house is $. (Round your response to the nearest dollar.)
What is the loss in value if a homeowner lets his house run down so that its condition becomes "poor"?
The loss is $. (Round your response to the nearest dollar.)
Compute the R² for the regression.
The R² for the regression is. (Round your response to three decimal places.)
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