Reference no: EM132198131

Account Balance 8976 8308 10028 11256 9869 10194 8706 9557 10565 9434 9687 9490 8806 9561 11757 9406 11150 7671 8803 9571 9566 7885 9773 9121 9298 10285 7801 9323 8643 12466 9447 10727 9243 9311 11033 11721 8727 8438 8317 8617 9052 10889 7766 9189

Income 63 37 52 64 47 74 49 58 70 69 25 57 46 48 80 66 46 28 53 52 77 32 55 52 43 65 38 52 36 85 64 86 57 68 74 82 24 37 55 50 39 73 26 47

Years of Education 12 14 16 15 17 15 12 14 16 11 18 15 14 16 15 14 15 12 13 15 12 14 11 15 14 15 12 14 16 15 14 15 15 12 14 16 15 15 12 14 16 15 14 15

Size of Household 2 2 2 4 2 2 2 2 3 3 3 1 3 2 3 2 3 2 1 2 3 3 1 2 3 2 1 2 3 2 2 2 3 2 3 2 3 3 2 1 3 3 1 2

The data in BUSI1013 Credit Card Balance.xlsx (as above) is collected for building a regression model to predict credit card balance of retail banking customers in a Canadian bank. Use this data to perform a simple regression analysis between Account balance and Income (in thousands).

1. Develop a scatter diagram using Account Balance as the dependent variable y and Income as the independent variable x.
2. Develop the estimated regression equation.
3. Use the estimated regression equation to predict the Account Balance of a customer with Income of $58 thousands.
4. Use the critical-value approach to perform an F test for the significance of the linear relationship between account balance and Income at the 0.05 level of significance.
5. What percentage of the variability of Account Balance can be explained by its linear relationship with Income?
6. Use the p-value approach to perform a t test for the significance of the linear relationship between Account Balance and Income at the 0.05 level of significance