A bank is interested in identifying different attributes of its customers, and below is the sample data of 150 customers. In the data table for the dummy variable Gender, 0 represents Male and 1 represents Female.And for the dummy variable Personal loan, 0 represents a customer who has not taken a personal loan and 1 represents a customer who has taken a personal loan. You will need to transfer data to an Excel format.

Age	Gender	Work experience	Income (in $1000s)	Family size	Personal loan
47	0	22	53	3	1
26	1	3	22	1	1
38	0	16	29	4	1
37	0	12	32	6	1
44	0	22	32	3	0
55	1	30	45	7	0
44	1	23	50	2	0
30	1	5	22	2	0
63	0	35	56	2	0
34	1	8	23	4	0
52	0	26	29	1	1
55	0	25	34	2	1
52	0	28	45	3	1
63	1	29	23	3	1
51	1	30	32	4	0
41	0	18	21	5	1
37	0	14	43	4	1
46	0	23	23	3	1
30	1	6	18	3	1
48	1	25	34	2	0
50	1	22	21	1	1
56	0	31	24	4	0
35	1	9	23	3	1
39	0	13	29	5	1
48	0	22	34	6	0
51	1	21	39	2	1
27	1	3	26	1	1
57	1	32	49	2	1
33	1	12	39	3	1
58	0	33	32	2	0
46	0	21	45	3	1
32	0	6	23	5	0
56	1	28	45	3	1
35	1	12	28	4	1
47	1	23	38	1	1
50	0	23	32	3	0
57	1	25	32	4	1
38	0	15	25	5	1
52	1	24	22	2	1
56	0	31	19	3	1
47	1	24	34	4	0
54	0	31	45	2	1
25	0	2	21	1	1
40	1	16	34	6	0
61	1	30	49	2	1
29	1	6	34	1	1
52	0	25	39	3	1
56	0	31	54	2	1
61	0	33	43	2	0
26	0	4	23	2	1
60	1	30	56	3	0
37	1	12	23	5	0
39	1	14	39	4	0
46	1	21	34	5	0
59	1	30	39	2	0
54	0	31	28	1	1
27	0	4	22	1	1
54	0	30	45	2	0
42	1	18	36	4	0
64	0	35	46	2	0
33	1	8	32	6	1
65	0	34	36	1	0
38	0	13	32	4	0
48	1	23	26	5	0
31	1	7	32	3	0
39	0	15	35	5	1
58	1	28	45	2	0
51	0	26	23	3	0
41	0	18	34	3	0
36	1	12	32	2	0
39	0	12	22	4	0
58	0	29	34	2	0
42	1	15	45	1	0
44	1	21	32	3	0
65	1	35	54	2	0
40	0	13	23	5	0
33	1	11	41	4	0
45	1	24	29	5	0
38	0	12	24	4	1
32	1	10	28	3	1
51	0	30	43	2	1
32	0	11	34	1	1
46	0	22	39	4	1
44	1	21	25	3	0
41	1	15	28	2	1
54	1	29	54	4	1
26	1	3	24	2	0
33	0	8	26	3	1
45	1	20	34	4	0
63	1	30	54	2	0
55	0	31	49	3	1
49	1	25	34	5	1
64	1	35	54	2	0
26	0	3	19	1	0
42	1	19	23	1	1
48	1	22	43	3	1
64	1	34	45	2	0
52	0	28	32	4	0
41	0	16	34	3	1
40	0	14	34	5	0
40	0	16	26	4	0
55	1	32	37	2	1
49	0	27	39	3	0
46	0	21	29	1	0
59	1	32	56	2	0
51	0	26	23	3	1
45	0	23	43	4	1
39	1	17	26	4	1
55	1	32	37	5	1
63	0	35	43	2	0
53	1	27	24	1	1
39	0	16	43	6	1
50	1	25	56	3	0
27	0	4	32	1	1
29	0	6	23	2	1
61	0	30	45	1	0
57	1	27	34	2	1
56	1	34	54	4	0
35	1	6	45	5	0
25	0	3	32	2	1
57	0	27	36	2	0
47	0	25	54	4	1
60	1	35	33	3	0
32	0	8	45	2	1
27	1	4	32	1	0
39	0	18	39	4	1
26	0	1	22	1	0
46	1	25	34	5	0
28	0	4	23	2	0
64	0	37	43	4	0
65	1	33	49	2	0
47	1	25	37	4	0
27	1	5	28	2	1
25	0	3	34	1	1
25	0	2	24	1	1
64	0	30	53	2	0
44	1	21	48	5	1
65	0	25	47	2	0
54	0	31	55	1	1
51	0	26	43	3	0
51	0	21	46	1	1
28	1	4	25	2	1
56	1	32	55	3	1
57	1	26	49	2	1
35	1	9	27	6	1
47	1	21	54	4	1
54	1	27	45	2	0
28	1	5	29	3	1
45	0	22	45	5	0
43	1	18	43	2	1

For the cutoff probability value 0.5, what value of k minimizes the overall error rate on the validation data? Explain the difference in the overall error rate on the training, validation, and test data. 12 Points

For cutoff probability values of 0.5, 0.4, 0.3, and 0.2, what are the corresponding Class 1 error rates and Class 0 error rates on the validation data? 12 Points