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2. Develop estimated regression equations, first using annual income as the independent variable and then using household size as the independent variable. Which variable is
2. 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.
3. Develop estimated regression equation with annual income and household size as the independent variables. Discuss your findings.
For parts 2 &3 after you run the regression:
- First interpret the coefficients.
- Run a t-test for the coefficients (Critical value and p-value approach).
- Interpret R Square, Standard error.
- Construct a confidence interval for the coefficients.
Income ($1000s) | Household Size | Amount Charged ($) |
54 | 3 | 4,016 |
30 | 2 | 3,159 |
32 | 4 | 5,100 |
50 | 5 | 4,742 |
31 | 2 | 1,864 |
55 | 2 | 4,070 |
37 | 1 | 2,731 |
40 | 2 | 3,348 |
66 | 4 | 4,764 |
51 | 3 | 4,110 |
25 | 3 | 4,208 |
48 | 4 | 4,219 |
27 | 1 | 2,477 |
33 | 2 | 2,514 |
65 | 3 | 4,214 |
63 | 4 | 4,965 |
42 | 6 | 4,412 |
21 | 2 | 2,448 |
44 | 1 | 2,995 |
37 | 5 | 4,171 |
62 | 6 | 5,678 |
21 | 3 | 3,623 |
55 | 7 | 5,301 |
42 | 2 | 3,020 |
41 | 7 | 4,828 |
54 | 6 | 5,573 |
30 | 1 | 2,583 |
48 | 2 | 3,866 |
34 | 5 | 3,586 |
67 | 4 | 5,037 |
50 | 2 | 3,605 |
67 | 5 | 5,345 |
55 | 6 | 5,370 |
52 | 2 | 3,890 |
62 | 3 | 4,705 |
64 | 2 | 4,157 |
22 | 3 | 3,579 |
29 | 4 | 3,890 |
39 | 2 | 2,972 |
35 | 1 | 3,121 |
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