A real estate analyst believes that the three main factors that influence an apartment's rent in a college town are the number of bedrooms, the number of bathrooms, and the apartment's square footage. For 40 apartments, she collects data on the rent (y, in $), the number of bedrooms (x1), the number of bathrooms (x2), and its square footage (x3). She estimates the following model as Rent= Bo + ß1 Bedroom + B2 Bath + B3 Sqft + ɛ. The following ANOVA table shows a portion of the regression results. df MS F Regression 3 5,694,798 1,898,266 50.88 Residual 36 1,343,142 37,310 Total 39 7,037,940 Coefficients Standard Error t-stat p-value Intercept 280 106.0 2.64 0.0030 Bedroom 218 57.5 3.79 0.0005 Bath 95 53.8 1.77 0.1172 Sqft 0.4 0.1 4 0.0284 The slope coefficient for Bedroom indicates that, holding other explanatory variables constant, Multiple Choice for each additional bedroom the rent is predicted to increase by $0.40 for each additional bedroom the rent is predicted to increase by $218

A real estate analyst believes that the three main factors that influence an apartment's rent in a college town are the number of bedrooms, the number of bathrooms, and the apartment's square footage. For 40 apartments, she collects data on the rent (y, in $), the number of bedrooms (x1), the number of bathrooms (x2), and its square footage (x3). She estimates the following model as Rent= Bo + ß1 Bedroom + B2 Bath + B3 Sqft + ɛ. The following ANOVA table shows a portion of the regression results. df MS F Regression 3 5,694,798 1,898,266 50.88 Residual 36 1,343,142 37,310 Total 39 7,037,940 Coefficients Standard Error t-stat p-value Intercept 280 106.0 2.64 0.0030 Bedroom 218 57.5 3.79 0.0005 Bath 95 53.8 1.77 0.1172 Sqft 0.4 0.1 4 0.0284 The slope coefficient for Bedroom indicates that, holding other explanatory variables constant, Multiple Choice for each additional bedroom the rent is predicted to increase by $0.40 for each additional bedroom the rent is predicted to increase by $218

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Description: The slope coefficient for Bedroom indicates that, holding other explanatory variables constant,Multiple Choicefor each additional bedroom the rent is predicted to increase by $0.40for each additional bedroom the rent is predicted to increase by $218

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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Question

The slope coefficient for Bedroom indicates that, holding other explanatory variables constant,
Multiple Choice
for each additional bedroom the rent is predicted to increase by $0.40
for each additional bedroom the rent is predicted to increase by $218
for each additional bedroom the rent is predicted to increase by $280
for each additional bedroom the rent is predicted to increase by $95

A real estate analyst believes that the three main factors that influence an apartment's rent in a college town are the number of bedrooms, the number of
bathrooms, and the apartment's square footage. For 40 apartments, she collects data on the rent (y, in $), the number of bedrooms (x1), the number of
bathrooms (x2), and its square footage (x3). She estimates the following model as Rent = Bo + ß1 Bedroom + B2 Bath + B3 Sqft + ɛ. The following
ANOVA table shows a portion of the regression results.
df
MS
Regression
3
5,694,798
1,898,266
50.88
Residual
36
1,343,142
37,310
Total
39
7,037,940
Coefficients
Standard Error
t-stat
p-value
Intercept
280
106.0
2.64
0.0030
Bedroom
218
57.5
3.79
0.0005
Bath
95
53.8
1.77
0.1172
Sqft
0.4
0.1
4
0.0284
The slope coefficient for Bedroom indicates that, holding other explanatory variables constant,
Multiple Choice
for each additional bedroom the rent is predicted to increase by $0.40
for each additional bedroom the rent is predicted to increase by $218

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