2. Use the regression tool in Data Analysis to develop a regression model using

Question

2. Use the regression tool in Data Analysis to develop a regression model using account balance as the dependent variable and ATM use per month as the independent variable.

            a) What is the coefficient on the independent variable? Interpret this in your own words.

            b) Is this statistically significant at the 95% level? How do you know?

            c) Predict the customer’s account balance if they use the ATM 5 times per month.

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

Q2:

SUMMARY OUTPUT Regression Statistics Multiple R 0.7089 R Square 0.502539 Adjusted R Square 0.493962 Standard Error 424.6162 Observations 60 ANOVA df SS MS F Significance F Regression 1 10564096 10564096 58.59211781 2.33E-10 Residual 58 10457337 180298.9 Total 59 21021433 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 485.2097 143.4437 3.38258 0.001291648 198.076 772.3435 198.076 772.3435 ATM 98.51038 12.86952 7.654549 0.000000000233 72.74923 124.2715 72.74923 124.2715 a) Regression : CAB = 485.2+98.51ATM b) the p-value is very small =0.00 also the t value is >3 therefore otright rejected at all levels of significance. The 95% confidence interval also contains the value of ATMcoefficient therefore statistically significant. c) AT ATM = 5 CAB = 485.2+98.51*5 CAB = 977.75

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