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BUAD 310 In-Class Practice
11/3/10
The
t
Table that we used in class is attached.
A local grocery store wants to predict the daily sales in dollars. The manager believes that the amount
of newspaper advertising significantly affects the store sales. He randomly selected some data
consisting of daily grocery store sales (
Sales
, response variable, in thousands of dollars) and advertising
expenditures (
Advertising
, explanatory variable, in thousands of dollars). Use the following Minitab
output to answer questions
1-7
. Note that some of the output is missing.
Predictor
Coef
SE Coef
T
P
Constant
63.3333
7.9682
Advertising
6.6667
1.6667
S =
R-Sq =
R-Sq(adj) =
Analysis of Variance
Source
DF
SS
MS
F
P
Regression
1
0.0103
Residual Error
5
666.667
Total
6
2800.000
1.
The value of the explained variation
SSR
is
A)
666.667
B)
6.6667
C)
2133.333
D)
2800.000
E)
5
2.
The value of the
r
-squared
is
A)
76.2%
B)
23.8%
C)
87.3%
D)
48.8%
E)
1.31
3.
The value of
s
is
A)
1.6667
B)
10.541

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C)
7.9682
D)
11.547
E)
133.3334
4.
The formula for a
point prediction
for the daily grocery store sales when the advertising
expenditure is 10 thousand dollars is
A)
6.6667 + 63.3333 (10)
B)
63.3333 + 6.6667 (10)
C)
7.9682 + 1.6667 (10)
D)
1.6667 + 7.9682 (10)
E)
6.6667 + 1.6667 (10)
5.
Give the value of the
t
-statistic
for testing H
0
:
β
1
= 0 vs. H
a
:
β
1
≠ 0 and make a decision at the
1%
level
:
A)
0.250, do not reject the null hypothesis
B)
4.000, reject the null hypothesis
C)
4.000, do not reject the null hypothesis
D)

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