A
Last name:
Enter your LETTER answers HERE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
First name:
Note:
When done, using your LAST NAME and FIRST NAME
save THIS file as
E270Lastname Firstname TEST7
and e-mail it to
stowfig@iupui.edu
Questions 1-10 are related to the following data
Next 10 questions are based on the following data relating cases sold (millions) of the brand of soft drink to media
expenditure ($millions).
Case
Media
Sales
Expend.
Use the following calculations in the relevant formulas to
answer the questions
980
65
n=7
∑xy = 153,310
960
46
xx = 32
∑x² = 9,198
yx = 520
∑(x − xx )² = 2,030
∑(y − yx )² = 773,450
∑(y − ŷ)² = 105,248.57
180
18
115
10
1
A
B
C
D
The numerator of the slope coefficient formula for the estimated regression equation is:
36,830
37,930
39,030
40,130
A
B
C
D
The vertical intercept of the estimated regression equation is
-70.24
-60.57
40.65
60.88
2
3
The estimated regression equation predicts that for each additional $1 million in media expenditure, the case
sales would increase by ______ million.
A
9.62
B
12.85
C
14.69
D
18.14
4
A
B
C
D
The prediction error of case sales for media expenditure of $18 million is.
-86
-98
86
98
A
B
C
D
On average, the predicted case sales deviate from the observed case sales by,
126.5
135.2
145.1
158.3
5
6
The sum of squared explained deviations is,
A
B
C
D
7
680,322.9
668,201.4
652,080.0
635,958.6
A
B
C
D
The sample data provides that ______ fraction of variations in case sales is explained by media expenditure.
0.9571
0.9262
0.8639
0.8241
A
B
C
D
To standard error of the slope coefficient, se(b₁), is
1.26
1.99
2.89
3.22
8
9
The margin of error for a 95% confidence interval for the population slope parameter is,
A
6.28
B
7.28
C
8.28
D
9.28
10 To perform a test of hypothesis that the population slope parameter is zero, the test statistic t is
A
6.52
B
5.63
C
4.68
D
3.89
Use the following Excel regression output to answer the next 5 questions. The output shows the result of running a
regression relating costs to production volume. Fill in the highlighted cells first.
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
6
ANOVA
df
Regression
Residual
Total
Intercept
PRODVAL
SS
MS
1
5
F
160.071587
Signif F
2.25E-04
184775.04
7579083
Coefficients Std Error
617.662
428.31
8.755
t Stat
1.442
P-value Lower 95% Upper 95%
0.2227
-571.51
1806.84
0.0002
11 The fraction of the variations in cost explained by production volume is:
A
0.9756
B
0.9345
C
0.9038
D
0.8774
12 The predicted total cost when production volume is 1,000 is,
A
8,581
B
8,827
C
9,070
D
9,373
13
Given that the sum of the squared deviations of production volume is 96,470.83, the standard error of
the slope coefficient is
A
1.076
B
0.884
C
0.692
D
0.488
14 We are 95% confident that the population slope parameter is between,
A
5.16
9.00
B
6.83
10.68
C
8.98
12.82
D
9.49
13.33
15 The value of the test statistic for H₀: β₁ = 0 is,
A
5.21
B
7.69
C
10.17
D
12.65
