Question

Consider the following data for Simmons store where it is postulated that the categorical variable Y=0,if the customer did not use the coupon and 1,if the customer used the coupon;and X= annual spending at Simmons’s store ($000s) annually. Run a logistic regression model and compute the probability for a customer using a coupon if he/she spends $5 (in $000’s) annually at Simmons store. Examine the output and evaluate the following r squared for the model.

Customer	Annual spending ($000s)	Coupon =0, if not used, 1 if used)
1	2.291	0
2	3.215	0
3	2.135	0
4	3.924	1
5	2.528	0
6	2.473	0
7	2.384	0
8	7.026	1
9	1.182	0
10	3.345	1
11	2.567	0
12	1.892	0
13	3.123	1
14	2.678	0
15	1.789	0
16	3.456	1
17	3.231	1
18	2.456	0
19	3.111	1
20	3.556	1
21	2.875	0
22	2.124	0

Answer 1

Hey below is the output of logistic regression that I ran using online statistical calculator.

you can also run this in R

code for R

//

x=c(2.291,
3.215,
2.135,
3.924,
2.528,
2.473,
2.384,
7.026,
1.182,
3.345,
2.567,
1.892,
3.123,
2.678,
1.789,
3.456,
3.231,
2.456,
3.111,
3.556,
2.875,
2.124
)
coupon=c(0,
0,
0,
1,
0,
0,
0,
1,
0,
1,
0,
0,
1,
0,
0,
1,
1,
0,
1,
1,
0,
0
)
data1=data.frame(x,coupon)
model = glm(coupon~x,
data = data1,
family = binomial(link="logit"))
summary(model)

//

I hope this helps you

Thanks