A real estate builder wishes to determine how house size (House) is influenced by family income (Income) and family size (Size). House size is measured in meter square and income is measured in IDR millions. The builder randomly selected 50 families and ran the multiple regression. Partial Microsoft Excel output is provided below: What is the population model of this regression problem?What is the sample estimates of the regression problem?Which of the independent variables in the model are significant at the 5% level?Formulate the hypothesis and explain the answer. Regression StatisticsMultiple R0.8479R Square0.7189Adjusted R Square0.7069Standard Error17.5571Observations50ANOVAdfSSMSFSignificance FRegression37043.323618521.66180.0000Residual14487.7627308.2503Total4951531.0863CoefficientsStandard Errort StatP-valueIntercept-5.51467.2273-0.76300.4493Income0.42620.039210.86680.0000Size5.54371.69493.27080.0020

A real estate builder wishes to determine how house size (House) is influenced by family income (Income) and family size (Size). House size is measured in meter square and income is measured in IDR millions. The builder randomly selected 50 families and ran the multiple regression. Partial

A real estate builder wishes to determine how house size (House) is influenced by family income (Income) and family size (Size). House size is measured in meter square and income is measured in IDR millions. The builder randomly selected 50 families and ran the multiple regression. Partial

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter4: Polynomial And Rational Functions

Section4.6: Variation

Problem 37E

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A: Solution

Question

What is the population model of this regression problem?
What is the sample estimates of the regression problem?
Which of the independent variables in the model are significant at the 5% level?

Formulate the hypothesis and explain the answer.

Regression Statistics
Multiple R
0.8479
R Square
0.7189
Adjusted R Square
0.7069
Standard Error
17.5571
Observations
50
ANOVA
df
SS
MS
F
Significance F
Regression
37043.3236
18521.6618
0.0000
Residual
14487.7627
308.2503
Total
49
51531.0863
Coefficients
Standard Error
t Stat
P-value
Intercept
-5.5146
7.2273
-0.7630
0.4493
Income
0.4262
0.0392
10.8668
0.0000
Size
5.5437
1.6949
3.2708
0.0020

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