Suppose that a researcher collects data on houses that have sold in a particular neighborhood over the past year and obtains the regression results in the table shown below. Dependent variable: In(Price) Regressor Size In(Size) In(Size)² Bedrooms Pool View Pool x View Condition Intercept Summary Statistics SER R² (1) 0.00047 (0.000039) 0.085 (0.035) 0.046 (0.033) 0.19 (0.046) 13.41 (0.073) (2) 0.69 0.72 (0.056) (0.091) (3) 0.13 (0.039) 6.62 (0.43) 0.081 0.082 (0.034) (0.037) 0.027 0.027 (0.033) (0.031) 0.0037 (0.039) 0.099 0.75 (4) 0.64 0.771 (2.05) (0.062) 0.0087 (0.19) 0.088 0.084 (0.038) (0.035) 0.027 0.027 (0.029) 0.14 0.16 (0.038) (0.036) 6.69 7.08 (0.57) (7.51) (5) Using the results in column (1), what is the expected increase in price of building a 500-square-foot addition to a house, holding everything else in the model constant? 0.103 0.72 0.102 0.74 Variable definitions: Price = sale price (S); Size = house size (in square feet); Bedrooms = number of bedrooms; Pool = binary variable (1 if house has a swimming pool, 0 otherwise); View = binary variable (1 if house has a nice view, 0 otherwise); Condition = binary variable (1 if real estate agent reports house is in excellent condition, 0 otherwise). 0.108 0.73 (0.032) 0.0028 (0.15) 0.21 (0.037) 6.61 (0.43) 0.107 0.76 The expected increase in price of building a 500-square-foot addition to a house is % (Express your response as a percentage and round to two decimal places)
Suppose that a researcher collects data on houses that have sold in a particular neighborhood over the past year and obtains the regression results in the table shown below. Dependent variable: In(Price) Regressor Size In(Size) In(Size)² Bedrooms Pool View Pool x View Condition Intercept Summary Statistics SER R² (1) 0.00047 (0.000039) 0.085 (0.035) 0.046 (0.033) 0.19 (0.046) 13.41 (0.073) (2) 0.69 0.72 (0.056) (0.091) (3) 0.13 (0.039) 6.62 (0.43) 0.081 0.082 (0.034) (0.037) 0.027 0.027 (0.033) (0.031) 0.0037 (0.039) 0.099 0.75 (4) 0.64 0.771 (2.05) (0.062) 0.0087 (0.19) 0.088 0.084 (0.038) (0.035) 0.027 0.027 (0.029) 0.14 0.16 (0.038) (0.036) 6.69 7.08 (0.57) (7.51) (5) Using the results in column (1), what is the expected increase in price of building a 500-square-foot addition to a house, holding everything else in the model constant? 0.103 0.72 0.102 0.74 Variable definitions: Price = sale price (S); Size = house size (in square feet); Bedrooms = number of bedrooms; Pool = binary variable (1 if house has a swimming pool, 0 otherwise); View = binary variable (1 if house has a nice view, 0 otherwise); Condition = binary variable (1 if real estate agent reports house is in excellent condition, 0 otherwise). 0.108 0.73 (0.032) 0.0028 (0.15) 0.21 (0.037) 6.61 (0.43) 0.107 0.76 The expected increase in price of building a 500-square-foot addition to a house is % (Express your response as a percentage and round to two decimal places)
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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R2
Transcribed Image Text:Suppose that a researcher collects data on houses that have sold in a particular neighborhood over the past year and obtains the regression results in the table shown below.
Dependent variable: In(Price)
Regressor
Size
In(Size)
In(Size)²
Bedrooms
Pool
View
Pool x View
Condition
Intercept
Summary Statistics
SER
Ŕ²
(1)
0.00047
(0.000039)
0.085
(0.035)
0.046
(0.033)
0.19
(0.046)
13.41
(0.073)
(2)
(3)
0.72
0.69
(0.056) (0.091)
0.0037
(0.039)
0.099
0.75
0.13 0.16
(0.039) (0.038)
6.62
(0.43)
0.081
0.088
0.082
(0.034) (0.037) (0.038)
0.027
0.027 0.027
(0.033)
(0.031)
(0.029)
(4)
0.64
(2.05)
0.0087
(0.19)
0.14
(0.036)
6.69 7.08
(0.57) (7.51)
Using the results in column (1), what is the expected increase in price of building a 500-square-foot addition to a house, holding everything else in the model constant?
0.108
0.73
(5)
0.771
(0.062)
0.084
(0.035)
0.027
(0.032)
0.0028
(0.15)
0.21
(0.037)
6.61
(0.43)
0.103
0.102
0.74
0.72
Variable definitions: Price = sale price (S); Size = house size (in square feet); Bedrooms = number
of bedrooms; Pool = binary variable (1 if house has a swimming pool, 0 otherwise); View = binary
variable (1 if house has a nice view, 0 otherwise); Condition = binary variable (1 if real estate
agent reports house is in excellent condition, 0 otherwise).
0.107
0.76
The expected increase in price of building a 500-square-foot addition to a house is %
(Express your response as a percentage and round to two decimal places)
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