Subset the data to include only those individuals who lived in an urban area Predict whether or not an individuals marriage will end up in a divorce, a separation, or a remarriage using predictor variables such as sex, parents education, height, weight, number of years of education, self esteem scale, and whether the person is outgoing as a kid and or adult ID Age Urban Mother Edu Father Edu Siblings Black Hispanic White Christian WomenPlace Male FamilySize Self Esteem Height Weight Outgoing Kid Outgoing Adult HealthPlan Income Marital Status Education WeeksEmployed 1 21 1 8 8 1 0 0 1 1 0 0 5 65 2 20 1 5 8 8 0 0 1 1 1 0 5 16 62 120 0 1 1 0 1 12 0 3 18 1 10 12 3 0 0 1 1 0 0 5 20 1 1 1 0 1 12 52 4 17 1 11 12 3 0 0 1 1 0 0 5 67 110 0 1 5 20 1 12 12 1 0 0 1 1 0 1 4 23 63 130 6 19 1 12 12 1 0 0 1 1 0 1 4 27 64 200 1 1 1 40000 1 16 52 7 15 1 12 12 1 0 0 1 1 0 1 3 26 65 131 0 1 1 25000 3 12 52 8 21 1 9 6 7 0 0 1 0 0 0 3 23 65 179 1 1 1 27400 3 13 52 9 16 1 12 10 4 0 0 1 1 0 1 6 26 66 145 1 1 1 52000 1 14 52 10 19 1 12 12 3 0 0 1 1 0 0 3 19 66 115 0 1 11 20 1 12 12 1 0 0 1 1 0 1 3 71 155 1 1 1 55000 0 16 52 12 20 1 15 12 3 0 0 1 1 0 0 3 30 66 118 0 1 13 21 1 12 16 2 0 0 1 1 0 1 5 25 71 180 0 1 1 60000 2 16 52 14 16 1 12 12 2 0 0 1 1 0 0 5 21 67 135 1 1 1 48000 2 18 52 15 15 1 12 12 1 0 0 1 1 0 1 4 23 73 185 1 0 1 0 1 16 0 16 21 1 12 12 3 0 0 1 1 0 0 4 25 63 130 1 1 1 38000 1 13 52 17 22 1 12 15 2 0 0 1 0 0 1 2 24 69 160 1 1 0 48000 0 13 52 18 21 1 12 16 2 0 0 1 0 0 1 1 28 69 155 1 1 1 120000 3 13 52 19 22 1 10 12 3 0 0 1 1 0 0 2 28 64 120 1 1 20 20 1 12 18 2 0 0 1 1 0 0 5 21 64 120 0 1 1 52000 1 17 52 21 18 1 12 18 2 0 0 1 1 0 0 5 28 62 133 1 1 1 82000 1 16 52 22 16 1 12 12 1 0 0 1 1 0 0 4 17 64 110 0 1 1 36000 1 16 52 23 21 1 12 12 2 0 0 1 1 0 1 5 72 175 24 18 1 12 12 2 0 0 1 1 0 1 5 28 71 180 1 1 25 20 1 14 16 1 0 0 1 0 0 0 3 19 67 125 0 1 1 20000 1 14 52 26 17 1 16 17 2 0 0 1 1 0 1 4 25 67 136 1 1 27 19 1 14 20 1 0 0 1 1 0 0 4 23 63 123 1 1 1 13126 1 16 44 28 15 1 14 20 1 0 0 1 0 0 0 4 19 65 114 0 1 1 24000 3 13 52 29 19 1 0 4 1 0 0 1 0 1 0 4 30 67 146 0 1 1 50000 1 12 52

Question: Subset the data to include only those individuals who lived in an urban area. Predict whether or not an individuals marriage will end up in

Subset the data to include only those individuals who lived in an urban area. Predict whether or not an individual’s marriage will end up in a divorce, a separation, or a remarriage using predictor variables such as sex, parents’ education, height, weight, number of years of education, self-esteem scale, and whether the person is outgoing as a kid and/or adult.

ID	Age	Urban	Mother_Edu	Father_Edu	Siblings	Black	Hispanic	White	Christian	WomenPlace	Male	FamilySize	Self_Esteem	Height	Weight	Outgoing_Kid	Outgoing_Adult	HealthPlan	Income	Marital_Status	Education	WeeksEmployed
1	21	1	8	8	1	0	0	1	1	0	0	5		65
2	20	1	5	8	8	0	0	1	1	1	0	5	16	62	120	0	1	1	0	1	12	0
3	18	1	10	12	3	0	0	1	1	0	0	5	20			1	1	1	0	1	12	52
4	17	1	11	12	3	0	0	1	1	0	0	5		67	110	0	1
5	20	1	12	12	1	0	0	1	1	0	1	4	23	63	130
6	19	1	12	12	1	0	0	1	1	0	1	4	27	64	200	1	1	1	40000	1	16	52
7	15	1	12	12	1	0	0	1	1	0	1	3	26	65	131	0	1	1	25000	3	12	52
8	21	1	9	6	7	0	0	1	0	0	0	3	23	65	179	1	1	1	27400	3	13	52
9	16	1	12	10	4	0	0	1	1	0	1	6	26	66	145	1	1	1	52000	1	14	52
10	19	1	12	12	3	0	0	1	1	0	0	3	19	66	115	0	1
11	20	1	12	12	1	0	0	1	1	0	1	3		71	155	1	1	1	55000	0	16	52
12	20	1	15	12	3	0	0	1	1	0	0	3	30	66	118	0	1
13	21	1	12	16	2	0	0	1	1	0	1	5	25	71	180	0	1	1	60000	2	16	52
14	16	1	12	12	2	0	0	1	1	0	0	5	21	67	135	1	1	1	48000	2	18	52
15	15	1	12	12	1	0	0	1	1	0	1	4	23	73	185	1	0	1	0	1	16	0
16	21	1	12	12	3	0	0	1	1	0	0	4	25	63	130	1	1	1	38000	1	13	52
17	22	1	12	15	2	0	0	1	0	0	1	2	24	69	160	1	1	0	48000	0	13	52
18	21	1	12	16	2	0	0	1	0	0	1	1	28	69	155	1	1	1	120000	3	13	52
19	22	1	10	12	3	0	0	1	1	0	0	2	28	64	120	1	1
20	20	1	12	18	2	0	0	1	1	0	0	5	21	64	120	0	1	1	52000	1	17	52
21	18	1	12	18	2	0	0	1	1	0	0	5	28	62	133	1	1	1	82000	1	16	52
22	16	1	12	12	1	0	0	1	1	0	0	4	17	64	110	0	1	1	36000	1	16	52
23	21	1	12	12	2	0	0	1	1	0	1	5		72	175
24	18	1	12	12	2	0	0	1	1	0	1	5	28	71	180	1	1
25	20	1	14	16	1	0	0	1	0	0	0	3	19	67	125	0	1	1	20000	1	14	52
26	17	1	16	17	2	0	0	1	1	0	1	4	25	67	136	1	1
27	19	1	14	20	1	0	0	1	1	0	0	4	23	63	123	1	1	1	13126	1	16	44
28	15	1	14	20	1	0	0	1	0	0	0	4	19	65	114	0	1	1	24000	3	13	52
29	19	1	0	4	1	0	0	1	0	1	0	4	30	67	146	0	1	1	50000	1	12	52

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