Please check all files.
>Sheet = Male; 1 = Female)
8
88
3 1 98
5 1 4 1 91
20
5 1 01
5 0 5
5 0 9
34 5 0 6 0 7 0 39 5 1 65 3
5 1 3
4 1 85
48 9
2 1 2 0 57 5 1 60
71 041
2 0 47 7
4 1 47 3 1 4 0 63 00
5 1 24 3 1 6 0 3
24 4 0 38 6 1 44
54 5 1 08
28 5 1 58 4 0 14
5 1 48 6 1 26 5 1 4 0 12
29 2 1 21
75 5 1 4 0 3 1 56 6 0 30 3 1 57 8
2 0 41 5 1 23 5 0 00
28 5 0 25
23 5 0 70
45 5 1 33 4 1 42 1 1 39 4 1 60 1 0 57 5 0 41 5 0 67 5 0 73 5 1 57 5 1 64 711
4 0 24 5 1 25 4 1 34 6 0 78 5 1 34 5 1 34 2 1 41 3 0 62 1 1 57 3 0 23 5 1 78 4 0 36 4 0 44 5 1 75 5 0 70 4 1 38 5 0 35 4 0 65 4 0 68 6 0 48 5 1 24 5 0 46 5 0 43 5 1 58 5 0 66 5 1 68 4 1 74 5 1 32 2 0 61 5 0 42 5 1 60 5 0 64 6 1 53 2 1 62 5 1 78 5 0 44 2 0 58 5 1 27 3 1 68 5 1 4 1 70 5 1 38 5 1 25 5 1 30 6 1 70 5 1 37 5 0 40 5 0 29 5 0 54 4 0 52 5 1 65 2 0 72 4 1 40 5 0 36 4 1 43 4 0 38 5 1 73 1 1 41 4 1 35 2 1 21 3 1 59 5 1 56 5 1 42 5 1 46 4 1 34 4 1 70 6 0 55 5 0 38 2 0 51 4 1 66 5 0 43 5 0 >Data
2 : Business Analytics and Decision Making
: SLP Template
0 Module 4 SLP Template, Doe
= Female)
88
3 1 8
5 1 4 1 91
20
5 1 01
5 0 5
5 0 9
34 5 0 6 0 7 0 39 5 1 65 3
5 1 48 3
4 1 85
48 9
2 1 2 0 57 5 1 60
71 041
2 0 47 7
4 1 47 3 1 4 0 63 5 1 24 3 1 6 0 3
24 4 0 38 6 1 44
54 5 1 08
28 5 1 58 4 0 14
5 1 48 6 1 26 5 1 52 4 0 12
29 2 1 21
75 5 1 4 0 3 1 56 6 0 30 3 1 57 8
2 0 41 5 1 23 5 0 00
28 5 0 25
23 5 0 70
45 5 1 33 4 1 42 1 1 39 4 1 60 1 0 57 5 0 41 5 0 67 5 0 73 5 1 57 5 1 64 711
4 0 24 5 1 25 4 1 34 6 0 78 5 1 34 5 1 34 2 1 41 3 0 62 1 1 57 3 0 23 5 1 78 4 0 36 4 0 44 5 1 75 5 0 70 4 1 38 5 0 35 4 0 65 4 0 68 6 0 48 5 1 24 5 0 46 5 0 43 5 1 58 5 0 66 5 1 68 4 1 74 5 1 32 2 0 61 5 0 42 5 1 60 5 0 64 6 1 53 2 1 62 5 1 78 5 0 44 2 0 58 5 1 27 3 1 68 5 1 4 1 70 5 1 38 5 1 25 5 1 30 6 1 70 5 1 37 5 0 40 5 0 29 5 0 54 4 0 52 5 1 65 2 0 72 4 1 40 5 0 36 4 1 43 4 0 38 5 1 73 1 1 41 4 1 35 2 1 21 3 1 59 5 1 56 5 1 42 5 1 46 4 1 34 4 1 70 6 0 55 5 0 38 2 0 51 4 1 66 5 0 43 5 0 0
MODULE 4, BUS 520
The primary resource for this module is Introductory Business Statistics, by Alexander, Illowsky, and Dean. Alexander, H., Illowsky, B., & Dean, S. (2017). Introductory Business Statistics. Openstax. Retrieved from
https://openstax.org/details/books/introductory-business-statistics
Include APA citations from this resource
ASSIGNMENT 1
Module 4 – Case
MULTIVARIATE ESTIMATION AND MODEL FIT
Assignment Overview
You are a consultant who works for the Diligent Consulting Group. In this Case, you are engaged on a consulting basis by Loving Organic Foods. In order to get a better idea of what might have motivated customers’ buying habits you are asked to analyze the factors that impact organic food expenditures. You performed a simple linear regression analysis in the Module 3 Case. Now, you are adding a layer of complexity to that analysis and including more independent variables in your model. (Mod3 Case is attached Case_3_Excel & Case_3_Word)
Case Assignment
Using Excel, generate regression estimates for the following model:
Annual Amount Spent on Organic Food = α + b1Age + b2AnnualIncome After you have reviewed the results from the estimation, write a report to your boss that interprets the results that you obtained. Please include the following in your report: 1. The regression output you generated in Excel. 2. Your interpretation of the coefficient of determination (r-squared). 3. Your interpretation of the global test for statistical significance (the F-test). 4. Your interpretation of the coefficient estimates for all the independent variables. 5. Your interpretation of the statistical significance of the coefficient estimates for all the independent variables. 6. The regression equation with estimates substituted into the equation. (Note: Once the estimates are substituted into the regression equation, it should take a form similar to this: y = 10 +2×1 +1×2 +4×3 +0.9×4) 7. An estimate of “Annual Amount Spent on Organic Food” for the average consumer. (Note: You will need to substitute the averages for all the independent variables into the regression equation for x, the intercept for α, and solve for y.) 8. A discussion of whether or not the coefficient estimate on the Age variable in this estimation is different than it was in the simple linear regression model from Module 3 Case. Be sure to explain why it did/did not change. 9. You decide you want to generate an elasticity coefficient, so you log the following variables in Excel: Annual Amount Spent on Organic Food, Annual Income. 10. Using Excel, generate regression estimates for the following model:
Log(Annual Amount Spent on Organic Food) = α +b1Age + b2Log(AnnualIncome) 11. Your interpretation of the coefficient estimate for Log(AnnualIncome). 12. Your interpretation of the coefficient of determination (r-squared) for this new model. Data: Download the Excel-based data file:
BUS520 Module 4 Case
. (File is attached)
Assignment Expectations
Written Report
Length requirements: 3–4 pages minimum (not including Cover and Reference pages). Note: You must submit 3–4 pages of written discussion and analysis. Provide a brief introduction to/background of the problem, similar to the introduction/background you provided in Module 1 through 3 Case submissions. Provide a brief comparison of simple linear regression and multiple linear regression. Provide a written analysis that addresses each of requirements listed under the “Case Assignment” section. Write clearly, simply, and logically. Use double-spaced, black Verdana or Times Roman font in 12 pt. type size. Please use keywords as headings to organize the report. Avoid redundancy and general statements such as “All organizations exist to make a profit.” Make every sentence count. Paraphrase the facts using your own words and ideas, employing quotes sparingly. Quotes, if absolutely necessary, should rarely exceed five words. Upload both your written report and Excel file to the Case 4 Dropbox. Assume once again that you are a consultant who works for the Diligent Consulting Group. You are continuing to work on the analysis of the customer database from Modules 1 through 3.
ASSIGNMENT 2
Complete the following tasks in the
Module 4 SLP
assignment template: 1. Compare the coefficients of determination (r-squared values) from the three linear regressions: simple linear regression from Module 3 Case, multivariate regression from Module 4 Case, and the second multivariate regression with the logged values from Module 4 Case. Which model had the “best fit”? 2. Calculate the residual for the first observation from the simple linear regression model. Recall, the Residual = Observed value – Predicted value or e = y – ŷ. 3. What happens to the overall distance between the best fit line and the coordinates in the scatterplot when the residuals shrink? 4. What happens to the coefficient of determination when the residuals shrink? 5. Consider the r-squared from the linear regression model and the r-squared from the first multivariate regression model. Why did the coefficient of determination change when more variables were added to the model?
2
1
Annual Amount Spent on Organic Food
Age
Annual Income
Number of People in Household
Gender (
0
7
3
4
77
109
6
11
5
47
109981
92
24
23
11
21
39
1
29
38
11
34
1
65
56
58
11
41
11
51
44
115100
10
46
11
63
30
179
33
75
116339
181
73
32
117907
12305
1190
71
9080
58
60
9113
48
58
62
61
61
57
64
70
49
62180
6000
62202
67
68
8579
68
40
7393
69618
8161
28
73079
10800
7
59
6160
77129
10800
66
79618
8
54
81131
17666
86246
1
26
89167
1
43
89576
97
37
92296
13301
27
9
36
18106
93954
11468
95937
9547
52
100846
78
103276
1
55
104112
7598
45
105119
7783
74
1059
25
17737
106084
7824
108616
6552
10903
11232
109585
6540
37834
42
38940
72
42145
53
48677
4476
48997
2800
49058
7839
49609
3472
53279
8854
53917
8900
54716
12791
126306
12712
130893
13321
134488
8802
1
35
14369
139701
7908
142014
17840
142857
15107
143182
12070
150987
6389
152041
6606
154702
6291
155552
7425
157329
11436
163794
7612
164108
7515
165851
13115
172497
11870
174458
8450
177517
16324
183779
9331
185111
9184
186467
16803
189137
10709
194351
14456
194380
16634
197358
12227
197400
13476
198650
14554
202859
9393
203591
14594
206216
6628
207679
11240
210498
13101
210678
14034
211249
17837
211961
7849
212851
10578
213035
11325
214457
7105
215442
16460
220178
8390
220403
14956
220893
10903 21
221223
12054
221498
11697
222618
12781
229072
17456
229685
12835
230228
13403
235617
15051
238087
14225
240768
11196
242529
11475
243765
5605
244625
9890
245208
13227
247648
11200
249805
9600
252033
15703
252812
6486
257143
9430
258167
7755
258640
8100
261020
14821
266223
10650
266269
12589
267565
11600
268380
13000
269431
17065
269839
16500
270441
8600
272795
11900
274846
16723
276250
16759
277231
2
Trident University
BUS
5
0
Module
4
FILL IN ALL CELLS THAT ARE HIGHLIGHTED IN YELLOW
Please remember to save this file with your last name in the file name. For example: BUS
52
Name:
Annual Amount Spent on Organic Food
Age
Annual Income
Number of People in Household
Gender (0 = Male;
1
7
3
48
77
109
6
11
59
47
109981
92
24
23
11
21
39
1
29
38
11
34
1
65
56
58
11
41
11
51
44
115100
10
46
11
63
30
179
33
75
116339
181
73
32
117907
12305
1190
71
9080
58
60
9113
58
62
61
61
57
64
70
49
62180
6000
62202
67
68
8579
68
40
7393
69618
8161
28
73079
10800
75900
6160
77129
10800
66
79618
8
54
81131
17666
86246
1
26
89167
1
43
89576
97
37
92296
13301
27
9
36
18106
93954
11468
95937
9547
100846
78
103276
1
55
104112
7598
45
105119
7783
74
1059
25
17737
106084
7824
108616
6552
10903
11232
109585
6540
37834
42
38940
72
42145
53
48677
4476
48997
2800
49058
7839
49609
3472
53279
8854
53917
8900
54716
12791
126306
12712
130893
13321
134488
8802
1
35
14369
139701
7908
142014
17840
142857
15107
143182
12070
150987
6389
152041
6606
154702
6291
155552
7425
157329
11436
163794
7612
164108
7515
165851
13115
172497
11870
174458
8450
177517
16324
183779
9331
185111
9184
186467
16803
189137
10709
194351
14456
194380
16634
197358
12227
197400
13476
198650
14554
202859
9393
203591
14594
206216
6628
207679
11240
210498
13101
210678
14034
211249
17837
211961
7849
212851
10578
213035
11325
214457
7105
215442
16460
220178
8390
220403
14956
220893
10903 21
221223
12054
221498
11697
222618
12781
229072
17456
229685
12835
230228
13403
235617
15051
238087
14225
240768
11196
242529
11475
243765
5605
244625
9890
245208
13227
247648
11200
249805
9600
252033
15703
252812
6486
257143
9430
258167
7755
258640
8100
261020
14821
266223
10650
266269
12589
267565
11600
268380
13000
269431
17065
269839
16500
270441
8600
272795
11900
274846
16723
276250
16759
277231
Question 1
FILL IN ALL CELLS THAT ARE HIGHLIGHTED IN YELLOW
QUESTION 1: Compare the coefficients of determination (r-squared values) from the three linear regressions: simple linear regression from Module 3 Case, multivariate regression from Module 4 Case, and the second multivariate regression with the logged values from Module 4 Case. Which model had the “best fit?”
R-squared from Module 3 Simple Linear Regression:
Adjusted R-squared from Module 4 Multivariate Linear Regression:
Adjusted R-squared from Module 4 Multivariate Regression with Logged Values:
Which model has the “best fit?” Recall: The coefficient of determination indicates how much of variation in the dependent variable we have explained in the model.
Questions 2-5
FILL IN ALL CELLS THAT ARE HIGHLIGHTED IN YELLOW
QUESTION 2: Calculate the residual for the first observation from the simple linear regression model. Recall, the Residual = Observed value – Predicted value or e = y – ŷ.
Observed value of y for the first observation from the dataset:
Predicted value of y for the first observation (Hint: To find this, substitute the actual value of x for the first observation into the regression equation and solve for y):
Residual:
QUESTION 3: What happens to the overall distance between the best fit line and the coordinates in the scatterplot when the residuals shrink?
QUESTION 4: What happens to the coefficient of determination when the residuals shrink?
QUESTION 5: Consider the r-squared from the linear regression model and the r-squared from the first multivariate regression model. Why did the coefficient of determination change when more variables were added to the model?
+ b3Number of People in Household + b4Gender
+ b3Number of People in Household + b4GenderSLP Assignment Expectations