Company is investigating the
relationship between the monthly Sales (in $) and the demographic
information about its customers. The demographic information are given
by the following variables
Age: Median age of customer base (in years)
HS: Percentage of customer base with a high school diploma
College: Percentage of customer base with a college degree
Growth: Annual population growth rate of customer base
Income: Median family income of customer base (in $)
Minitab full regression analyses were made and the results are shown
below:
Backward Elimination of Terms with
Candidate terms, Age, Growth, Income, HS, College
---Step 1---
--Step 2---
---Step 3---
Coef P
Coef
P
Coef P
---Step 4-
Coef P
-Step 5---
Coef
P
Constant
2270706
2248337
2384267
2126081
2969741
Age -27384
0.17 -28438 0.151-26107
0.15
-29076
1
0.17
8
0.96
Growth 2084
3
0.93
Income 2.4
2.1
0.944
7
0.08
HS
62735
0.01
62922
0.076 64498
3
60953
7
0.00
3
59660
0.00
2
College -570
0.84
-5103
0.839 -4732
0.84
2
5
S
848433
835508
823193
811809
802004
R-sq
24.45%
24.44%
24.43%
24.35%
24.05%
R-
12.64%
15.28%
17.76%
20.02%
sq(adj)
21.94%
Using the Backward elimination method with $α_{out}=0.25$, the final model
would have how many predictors?
