Case Problem 1 Consumer Research, Inc. Consumer Research, Inc., is an independent agency that conducts research on consumer attitudes and behaviors for a variety of firms. In one study, a client asked for an inves- tigation of consumer characteristics that can be used to predict the amount charged by credit card users. Data were collected on annual income, household size, and annual credit card charges for a sample of 50 consumers. The following data are contained in the file named Consumer. Income ($1000s) Household Size Household Amount Income ($1000s) Amount Size Charged ($) Charged ($) 54 3 4016 54 6. 5573 30 3159 30 1 2583 32 4 5100 48 2 3866 50 4742 34 3586 31 1864 67 4 5037 55 2 4070 50 3605 37 1 2731 67 5345 40 3348 55 5370 66 4 4764 52 3890 51 3 4110 62 3 4705 DATA file 25 3 4208 64 4157 Consumer 48 4 4219 22 3 3579 27 1 2477 29 3890 33 2 2514 39 2972 65 3 4214 35 1 3121 63 4 4965 39 4183 42 6. 4412 54 3 3730 21 2448 23 6. 4127 44 1 2995 27 2921 37 4171 26 7 4603 62 6. 5678 61 2 4273 21 3623 30 3067 55 7 5301 22 3074 42 3020 46 5 4820 41 4828 66 5149 Managerial Report 1. Use methods of descriptive statistics to summarize the data. Comment on the findings. 2. Develop estimated regression equations, first using annual income as the independ- ent variable and then using household size as the independent variable. Which vari- able is the better predictor of annual credit card charges? Discuss your findings. 3. Develop an estimated regression equation with annual income and household size as the independent variables. Discuss your findings. 4. What is the predicted annual credit card charge for a three-person household with an annual income of $40,000? 5. Discuss the need for other independent variables that could be added to the model. What additional variables might be helpful?
Case Problem 1 Consumer Research, Inc. Consumer Research, Inc., is an independent agency that conducts research on consumer attitudes and behaviors for a variety of firms. In one study, a client asked for an inves- tigation of consumer characteristics that can be used to predict the amount charged by credit card users. Data were collected on annual income, household size, and annual credit card charges for a sample of 50 consumers. The following data are contained in the file named Consumer. Income ($1000s) Household Size Household Amount Income ($1000s) Amount Size Charged ($) Charged ($) 54 3 4016 54 6. 5573 30 3159 30 1 2583 32 4 5100 48 2 3866 50 4742 34 3586 31 1864 67 4 5037 55 2 4070 50 3605 37 1 2731 67 5345 40 3348 55 5370 66 4 4764 52 3890 51 3 4110 62 3 4705 DATA file 25 3 4208 64 4157 Consumer 48 4 4219 22 3 3579 27 1 2477 29 3890 33 2 2514 39 2972 65 3 4214 35 1 3121 63 4 4965 39 4183 42 6. 4412 54 3 3730 21 2448 23 6. 4127 44 1 2995 27 2921 37 4171 26 7 4603 62 6. 5678 61 2 4273 21 3623 30 3067 55 7 5301 22 3074 42 3020 46 5 4820 41 4828 66 5149 Managerial Report 1. Use methods of descriptive statistics to summarize the data. Comment on the findings. 2. Develop estimated regression equations, first using annual income as the independ- ent variable and then using household size as the independent variable. Which vari- able is the better predictor of annual credit card charges? Discuss your findings. 3. Develop an estimated regression equation with annual income and household size as the independent variables. Discuss your findings. 4. What is the predicted annual credit card charge for a three-person household with an annual income of $40,000? 5. Discuss the need for other independent variables that could be added to the model. What additional variables might be helpful?
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Transcribed Image Text:Case Problem 1 Consumer Research, Inc.
Consumer Research, Inc., is an independent agency that conducts research on consumer
attitudes and behaviors for a variety of firms. In one study, a client asked for an inves-
tigation of consumer characteristics that can be used to predict the amount charged by
credit card users. Data were collected on annual income, household size, and annual
credit card charges for a sample of 50 consumers. The following data are contained in
the file named Consumer.
Income
Household
Amount
Income
Household
Amount
($1000s)
Size
Charged ($)
($1000s)
Size
Charged ($)
54
3
4016
54
6.
5573
30
3159
30
1
2583
32
4
5100
48
2
3866
3586
5037
50
4742
34
31
2
1864
67
4
55
2
4070
50
2
3605
37
1
2731
67
5345
40
2
3348
55
6.
5370
66
4
4764
52
2
3890
51
3
4110
62
3
4705
DATA file
25
3
4208
64
2
4157
Consumer
48
4
4219
22
3
3579
27
1
2477
29
3890
33
2
2514
39
2
2972
65
3
4214
35
1
3121
63
4
4965
39
4
4183
42
6.
4412
54
3
3730
21
2
2448
23
6.
4127
44
1
2995
27
2
2921
37
5
4171
26
7
4603
62
5678
61
2
4273
21
3
3623
30
2
3067
55
7
5301
22
4
3074
42
2
3020
46
5
4820
41
7
4828
66
4
5149
Managerial Report
1. Use methods of descriptive statistics to summarize the data. Comment on the findings.
2. Develop estimated regression equations, first using annual income as the independ-
ent variable and then using household size as the independent variable. Which vari-
able is the better predictor of annual credit card charges? Discuss your findings.
3. Develop an estimated regression equation with annual income and household size
as the independent variables. Discuss your findings.
4. What is the predicted annual credit card charge for a three-person household with
an annual income of $40,000?
5. Discuss the need for other independent variables that could be added to the model.
What additional variables might be helpful?
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