the comic book store owner is curious in how well radio and newspaper advertisements work. A sample of 22 counties with almost equal populations was gathered during the month. For each of the counties, the owner has set aside a particular sum for radio and newspaper advertising. Additionally, the owner was able to access comic book sales information for the stores he controlled in each municipality and classified it as Low or High. COUNTY (X1) Comic book Sales (X2) (0 = Low, 1 = High) Radio Ads (X3) (in thousands) Newspaper Ads (X4) (in thousands) 1 1 0 40 2 0 0 40 3 0 25 25 4 0 25 25 5 0 30 30 6 0 30 30 7 0 35 35 8 0 35 35 9 0 40 25 10 0 40 25 11 1 45 45 12 1 45 45 13 1 50 0 14 1 50 0 15 1 55 25 16 1 55 25 17 1 60 30 18 1 60 30 19 1 65 35 20 1 65 35 21 1 70 40 22 1 70 40 Interpret the Results of the Binary Logistic Regression found in the attached image files
the comic book store owner is curious in how well radio and newspaper advertisements work. A sample of 22 counties with almost equal populations was gathered during the month. For each of the counties, the owner has set aside a particular sum for radio and newspaper advertising. Additionally, the owner was able to access comic book sales information for the stores he controlled in each municipality and classified it as Low or High. COUNTY (X1) Comic book Sales (X2) (0 = Low, 1 = High) Radio Ads (X3) (in thousands) Newspaper Ads (X4) (in thousands) 1 1 0 40 2 0 0 40 3 0 25 25 4 0 25 25 5 0 30 30 6 0 30 30 7 0 35 35 8 0 35 35 9 0 40 25 10 0 40 25 11 1 45 45 12 1 45 45 13 1 50 0 14 1 50 0 15 1 55 25 16 1 55 25 17 1 60 30 18 1 60 30 19 1 65 35 20 1 65 35 21 1 70 40 22 1 70 40 Interpret the Results of the Binary Logistic Regression found in the attached image files
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
the comic book store owner is curious in how well radio and newspaper advertisements work. A sample of 22 counties with almost equal populations was gathered during the month. For each of the counties, the owner has set aside a particular sum for radio and newspaper advertising. Additionally, the owner was able to access comic book sales information for the stores he controlled in each municipality and classified it as Low or High.
|
COUNTY (X1)
|
Comic book Sales (X2) (0 = Low, 1 = High) |
Radio Ads (X3) (in thousands) |
Newspaper Ads (X4) (in thousands) |
|
1 |
1 |
0 |
40 |
|
2 |
0 |
0 |
40 |
|
3 |
0 |
25 |
25 |
|
4 |
0 |
25 |
25 |
|
5 |
0 |
30 |
30 |
|
6 |
0 |
30 |
30 |
|
7 |
0 |
35 |
35 |
|
8 |
0 |
35 |
35 |
|
9 |
0 |
40 |
25 |
|
10 |
0 |
40 |
25 |
|
11 |
1 |
45 |
45 |
|
12 |
1 |
45 |
45 |
|
13 |
1 |
50 |
0 |
|
14 |
1 |
50 |
0 |
|
15 |
1 |
55 |
25 |
|
16 |
1 |
55 |
25 |
|
17 |
1 |
60 |
30 |
|
18 |
1 |
60 |
30 |
|
19 |
1 |
65 |
35 |
|
20 |
1 |
65 |
35 |
|
21 |
1 |
70 |
40 |
|
22 |
1 |
70 |
40 |
Interpret the Results of the Binary Logistic Regression found in the attached image files
Transcribed Image Text:Block 1: Method = Enter
Omnibus Tests of Model Coefficients
Chi-square df Sig.
10.213 2 .006
10.213 2 .006
10.213 2 .006
Step 1 Step
Block
Model
Hosmer and Lemeshow Test
Step Chi-square df Sig.
1
29.754 8.000
-2 Log likelihood
Step
1
19.555a
.501
a. Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.
Step 1 1
2
3
4
5
6
7
8
9
10
Contingency Table for Hosmer and Lemeshow Test
Sales = Low
Sales = High
Observed Expected Observed Expected Total
1.958
.042 2
1.632
.368 2
1.413
.587 2
1.132
.868 2
.960
0 1.040 2
.671
2 1.329 2
.555
2
1.445 2
.323
2
1.677 2
.189
2
1.811 2
.167
4
3.833 4
Observed
Step 1 Sales
1
2
2
2
2
0
0
Step 1ª X3
X4
0
0
Low
High
Overall Percentage
Classification Tablea
a. The cut value is .500
1
0
이
Model Summary
Cox & Snell R Square
.105
Predicted
Sales
Low High Percentage Correct
7 2
77.8
1 12
92.3
86.4
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
.046 5.069| 11.024 1.110|
.018 .045 .157 1.692 1.018|
Constant -4.545 2.519 3.255 1.071 .011
a. Variable(s) entered on step 1: X3, X4.
.371
Nagelkerke R Square
95.0% C.I.for EXP(B)
Lower Upper
1.014
.933
1.216
1.111
Transcribed Image Text:Unweighted Casesa
Selected Cases
Unselected Cases
22
100.0
0
.0
22
100.0
0
.0
Total
22
100.0
a. If weight is in effect, see classification table for the total number of cases.
Low
High
Dependent Variable Encoding
Original Value Internal Value
Observed
Case Processing Summary
Step 0 Sales
Block 0: Beginning Block
Included in Analysis
Missing Cases
Total
0
1
Classification Tablea,b
Low
High
Overall Percentage
a. Constant is included in the model.
b. The cut value is .500
Step 0 Variables
Variables in the Equation
X3
Sales
Low High Percentage Correct
0 9
.0
0 13
B S.E. Wald df Sig. Exp(B)
Step 0 Constant.368.434 .719 1.396 1.444
Variables not in the Equation
Score df Sig.
Predicted
8.320 1 .004
N
X4 .000 11.000
Overall Statistics 8.391 2.015
Percent
100.0
59.1
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