3. Use the regression tool in Data Analysis to develop a regression to test whet

Question

3.   Use the regression tool in Data Analysis to develop a regression to test whether there are differences in Account Balance across city. Use Account Balance as your dependent variable and create a series of dummy variables to represent the city variable.

            a) How many dummy variables must you create to appropriately represent the four cities?

            b) Are any of your independent variables statistically significant at the 95% level? At the 90% level?

            c) Assume that all of your independent variables are statistically significant at the 95% level. Predict the average account balance for each of the four cities.

DATA to use:

Acct. Bal. # ATM tran. # services Debit card? Interest? City 1756 13 4 0 1 2 748 9 2 1 0 1 1501 10 1 0 0 1 1831 10 4 0 1 3 1622 14 6 0 1 4 1886 17 3 0 1 1 740 6 3 0 0 3 1593 10 8 1 0 1 1169 6 4 0 0 4 2125 18 6 0 0 2 1554 12 6 1 0 3 1474 12 7 1 0 1 1913 6 5 0 0 1 1218 10 3 1 0 1 1006 12 4 0 0 1 2215 20 3 1 0 4 137 7 2 0 0 3 167 5 4 0 0 4 343 7 2 0 0 1 2557 20 7 1 0 4 2276 15 4 1 0 3 1494 11 2 0 1 1 2144 17 3 0 0 3 1995 10 7 0 0 2 1053 8 4 1 0 3 1526 8 4 0 1 2 1120 8 6 1 0 3 1838 7 5 1 1 3 1746 11 2 0 0 2 1616 10 4 1 1 2 1958 6 2 1 0 2 634 2 7 1 0 4 580 4 1 0 0 1 1320 4 5 1 0 1 1675 6 7 1 0 2 789 8 4 0 0 4 1735 12 7 0 1 3 1784 11 5 0 0 1 1326 16 8 0 0 3 2051 14 4 1 0 4 1044 7 5 1 0 1 1885 10 6 1 1 2 1790 11 4 0 1 3 765 4 3 0 0 4 1645 6 9 0 1 4 32 2 0 0 0 3 1266 11 7 0 0 4 890 7 1 0 1 1 2204 14 5 0 0 2 2409 16 8 0 0 2 1338 14 4 1 0 2 2076 12 5 1 0 2 1708 13 3 1 0 1 2138 18 5 0 1 4 2375 12 4 0 0 2 1455 9 5 1 1 3 1487 8 4 1 0 4 1125 6 4 1 0 2 1989 12 3 0 1 2 2156 14 5 1 0 2 Column Full variable name A Account balance in $ B Number of ATM transactions last month C Number of other bank services used D Has a debit card (1 = yes, 0 = no) E Receives interest on the account (1 = yes, 0 = no) F Where banking is done 1 = Utica 2 = Schenectady 3 = Amsterdam 4 = Rome

Explanation / Answer

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 129.8020828 192.8286819 0.673147 0.503834496 -257.136967 516.7411327 -257.136967 516.7411327 ATM tran. 85.33625521 11.60815464 7.351406 1.36247E-09 62.04278931 108.6297211 62.04278931 108.6297211 services 57.69562731 26.44467112 2.181749 0.033670735 4.63051367 110.760741 4.63051367 110.760741 Debit card 143.3605618 100.7511676 1.422917 0.160732092 -58.81144219 345.5325659 -58.81144219 345.5325659 Interest 209.8107917 112.0150338 1.873059 0.066686273 -14.96381309 434.5853964 -14.96381309 434.5853964 Utica 43.94508299 143.9201426 0.305344 0.761323485 -244.851805 332.741971 -244.851805 332.741971 Schenectady 385.3655855 137.4070628 2.804554 0.007069174 109.638148 661.0930229 109.638148 661.0930229 Amsterdam -11.5682489 144.416653 -0.0801 0.936462601 -301.3614579 278.2249601 -301.3614579 278.2249601 a) we will create three dummy variable for four cities. b) Yes , Services is statistically significant at 5%. c) Results in table.

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