MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Researchers at a car resale company are trying to build a model to predict a car’s 4-
year resale value (in thousands of dollars) from several predictor variables. The variables they
selected follow.

a) What is the equation of the least-squares regression line? A particular car (not a
truck) cost $40,000 and has an engine of 3.8 liters. What do you predict the 4-year resale
value of this car will be?

b) Use α = 0.05 to test the significance of β1. Should x1 be dropped from the model?

c) Test if there exists any linear relationship between the dependent variable and any
of the independent variables, i.e., test H0 : B1=B2=B3= 0 at 5% significance level. 

Model
1
Engine
Data were collected on cars of different models made by different manufacturers. SPSS
output for the least-squares regression model is given below.
Model
1
Model
1
R
.962
Regression
Residual
Total
(Constant)
Type
Price
Engine
Model:
Type
Price
Model Summary
R Square
.926
0 if the vehicle is a car 1 if the vehicle is a
truck
The price of the vehicle in thousands of
dollars
The size of the engine
Sum of
Squares df
14568.642
3
1170.761 115
15739.404 118
B
ANOVA
897
643
.874
-1.893
Adjusted
R Square
.924
Unstandardized
Coefficients
Coefficients
Mean Square
Std. Error
,900
717
.028
.386
Std. Error of
the Estimate
3.191
F
Sig
4856.214 477.010 .000
10.181
95% Confidence Interval for B
Lower Bound Upper Bound
-.885
2.679
2.064
930
-1.129
-.777
.817
-2.658
Y₁ = Bo + B₁ X₁1 + B₂ X2i + B3 X31 + Ei
where
Y₁ = 4-year resale value, X₁1 = Type, X₂i = Price, X31 = Engine
Based on the SPSS output, answer the following questions:
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Transcribed Image Text:Model 1 Engine Data were collected on cars of different models made by different manufacturers. SPSS output for the least-squares regression model is given below. Model 1 Model 1 R .962 Regression Residual Total (Constant) Type Price Engine Model: Type Price Model Summary R Square .926 0 if the vehicle is a car 1 if the vehicle is a truck The price of the vehicle in thousands of dollars The size of the engine Sum of Squares df 14568.642 3 1170.761 115 15739.404 118 B ANOVA 897 643 .874 -1.893 Adjusted R Square .924 Unstandardized Coefficients Coefficients Mean Square Std. Error ,900 717 .028 .386 Std. Error of the Estimate 3.191 F Sig 4856.214 477.010 .000 10.181 95% Confidence Interval for B Lower Bound Upper Bound -.885 2.679 2.064 930 -1.129 -.777 .817 -2.658 Y₁ = Bo + B₁ X₁1 + B₂ X2i + B3 X31 + Ei where Y₁ = 4-year resale value, X₁1 = Type, X₂i = Price, X31 = Engine Based on the SPSS output, answer the following questions:
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