Consumer Research, Inc., is an independent agency that conducts research on consumer attitudes and behaviours for a variety of firms. In one study, a client asked for an investigation 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 20 consumers. Managerial Report: Use the regression technique, students need to include the following in their report. 1) Develop estimated regression equations, first using annual income as the independent variable and then using household size as the independent variable. Which variable is the better predictor of annual credit card charges? Discuss your findings. 2) Develop an estimated regression equation with annual income and household size as the independent variables. Discuss your findings. 3) Discuss the need for other independent variables that could be added to the model. What additional variables might be helpful? Income ($1000s) Household Size Amount Charged ($) 54 2 3348 65 2 4764 63 1 4110 42 2 4208 37 4 4219 62 3 2477 21 3 2514 40 4 3348 66 1 4764 51 2 4110 25 3 4208 48 4 4219 27 1 2477 33 2 2514 65 3 4214 63 4 4965 42 6 4412 37 2 2448 62 1 2995 21 5 4171
Case problem: Consumer Research, Inc.
Consumer Research, Inc., is an independent agency that conducts research on consumer attitudes and behaviours for a variety of firms. In one study, a client asked for an investigation 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 20 consumers.
Managerial Report: Use the regression technique, students need to include the following in their report.
1) Develop estimated regression equations, first using annual income as the independent variable and then using household size as the independent variable. Which variable is the better predictor of annual credit card charges? Discuss your findings.
2) Develop an estimated regression equation with annual income and household size as the independent variables. Discuss your findings.
3) Discuss the need for other independent variables that could be added to the model. What additional variables might be helpful?
| Income ($1000s) | Household Size | Amount Charged ($) |
| 54 | 2 | 3348 |
| 65 | 2 | 4764 |
| 63 | 1 | 4110 |
| 42 | 2 | 4208 |
| 37 | 4 | 4219 |
| 62 | 3 | 2477 |
| 21 | 3 | 2514 |
| 40 | 4 | 3348 |
| 66 | 1 | 4764 |
| 51 | 2 | 4110 |
| 25 | 3 | 4208 |
| 48 | 4 | 4219 |
| 27 | 1 | 2477 |
| 33 | 2 | 2514 |
| 65 | 3 | 4214 |
| 63 | 4 | 4965 |
| 42 | 6 | 4412 |
| 37 | 2 | 2448 |
| 62 | 1 | 2995 |
| 21 | 5 | 4171 |
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