5. How many districts were sampled in all? A) 21 C) 25 D) 26 6. What is the estimate for the error variance [? B) 24 C) 92.245 1937.137 A) 9.604 B) 12.960 D)

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The data referred to in this question were collected from several sales districts across the country.
The data represent sales for a maker of asphalt roofing shingles. Information on the following
variables is available:
Sales
Sales from last year in thousands of squares
Expenditures
Promotional expenditures in thousands of dollars
Accounts
Number of active accounts
Competing Brands
Number of competing brands producing equivalent or similar products
District Potential
A coded indicator of the potential of the district
(higher score = better potential)
Partial SPSS regression output of a multiple regression model with sales as the response variable
and the other four variables as predictor variables is given below:
ANOVA
Sum of
Model
Squares
df
Mean Square
F
Sig.
Regression
176777.1
4
44194.265
479.099
.000
Residual
1937.137
21
92.245
Total
178714.2
25
Coefficients
Unstandardized
Standardized
Coefficients
Coefficients
Model
Std. Error
Beta
t
Sig.
(Constant)
Promotional Expenditures
1
178.320
12.960
13.759
.00000
1.807
1.081
039
1.672
.10944
Number of Active Accounts
3.318
163
.558
20.368
.00000
Number of Competing Brands
-21.185
.788
-647
-26.887
.00000
District Potential
.325
468
018
.694
49544
M Notifications
91
M Inbox
Calendar
To Do
Transcribed Image Text:The data referred to in this question were collected from several sales districts across the country. The data represent sales for a maker of asphalt roofing shingles. Information on the following variables is available: Sales Sales from last year in thousands of squares Expenditures Promotional expenditures in thousands of dollars Accounts Number of active accounts Competing Brands Number of competing brands producing equivalent or similar products District Potential A coded indicator of the potential of the district (higher score = better potential) Partial SPSS regression output of a multiple regression model with sales as the response variable and the other four variables as predictor variables is given below: ANOVA Sum of Model Squares df Mean Square F Sig. Regression 176777.1 4 44194.265 479.099 .000 Residual 1937.137 21 92.245 Total 178714.2 25 Coefficients Unstandardized Standardized Coefficients Coefficients Model Std. Error Beta t Sig. (Constant) Promotional Expenditures 1 178.320 12.960 13.759 .00000 1.807 1.081 039 1.672 .10944 Number of Active Accounts 3.318 163 .558 20.368 .00000 Number of Competing Brands -21.185 .788 -647 -26.887 .00000 District Potential .325 468 018 .694 49544 M Notifications 91 M Inbox Calendar To Do
5. How many districts were sampled in all?
C)
A) 21
25
B) 24
D)
26
6. What is the estimate for the error variance 7?
A) 9.604
C)
92.245
B) 12.960
D)
1937.137
Transcribed Image Text:5. How many districts were sampled in all? C) A) 21 25 B) 24 D) 26 6. What is the estimate for the error variance 7? A) 9.604 C) 92.245 B) 12.960 D) 1937.137
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