Sample Exam 1
Part 1: Multiple Linear Regression:
1.
A regression line is fit from a sample of size 30.
The least squares line is:
2
1
*
2
.
13
*
7
.
4
2
.
2
ˆ
x
x
y
+
+
=
, and the standard errors of b1 and b2 are 3.1 and 2.8,
respectively.
a)
Give a 95% confidence interval for
2
β
.
b)
What is the test statistic for the test H0:
0
1
=
β
vs H:
0
1
≠
β
?
c)
Is X1 a significant linear predictor at the 5% level?
Why or why not?
Is X2 a
significant linear predictor at the 5% level?
Why or why not?
2.
Find the error in the following two statements:
a)
R square adjusted is not valid whenever there are categorical predictors in the
model.
b)
In multiple linear regression, the outcome variable Y is assumed to be normally
distributed.
3.
The following regression model was built to analyze the effect of having a corner
lot on the selling price of your home.
Saleprice is the dependent variable, and is
the actual selling price of the home (in thousands of dollars).
Assessed is the
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 Summer '08
 PORTER
 Regression Analysis, multiple linear regression, SalePrice, significant linear predictor

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