Question

1. Make a scatter diagram showing account balance on the y axis and ATM use per month on the x axis. Include a linear trendline and show the equation and R2 on the diagram.

   a) How much of the variation in account balances is explained by ATM use?

   b) Predict a customer’s account balance if they use the ATM 5 times per month?

   c) What is the predicted account balance if they use the ATM 6 times per month?

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.

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

Answer 1

1.

> model=lm(Acct..Bal.~X..ATM.tran.)
> summary(model)

Call:
lm(formula = Acct..Bal. ~ X..ATM.tran.)

Residuals:
Min 1Q Median 3Q Max
-1037.78 -244.84 10.42 297.02 881.73

Coefficients:
Estimate Std. Error t value Pr(>|t|)   
(Intercept) 485.21 143.44 3.383 0.00129 **
X..ATM.tran. 98.51 12.87 7.655 2.33e-10 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 424.6 on 58 degrees of freedom
Multiple R-squared: 0.5025, Adjusted R-squared: 0.494
F-statistic: 58.59 on 1 and 58 DF, p-value: 2.327e-10

a) R2 = 0.494 means that 49.4% of the total variation is explained by the regression model.

b) Predicted Account Balance = 485.21 + 98.51*5 = $977.76

c) Predicted Account Balance = 485.21 + 98.51*6 = $1076.27