Build a simple linear regression model to predict PSA level (Y) as a function of cancer volume (X).Use this model to predict the mean PSA level for a patient whose cancer volume is 20cc. In addition to building the simple linear regression model, the focus of this discussion is to assess the degree to which the assumptions of homoscedasticity and normalityare satisfied.

ID #	PSA Level	Cancer Vol.	Weight	AGE	BPH	SVI	CP	Gleason Score
1	0.651	0.5599	15.959	50	0	0	0	6
2	0.852	0.3716	27.66	58	0	0	0	7
3	0.852	0.6005	14.732	74	0	0	0	7
4	0.852	0.3012	26.576	58	0	0	0	6
5	1.448	2.117	30.877	62	0	0	0	6
6	2.16	0.3499	25.28	50	0	0	0	6
7	2.16	2.0959	32.137	64	1.8589	0	0	6
8	2.34	1.9937	34.467	58	4.6646	0	0	6
9	2.858	0.4584	34.467	47	0	0	0	7
10	2.858	1.2461	25.534	63	0	0	0	6
11	3.561	1.284	36.598	65	0	0	0	6
12	3.561	0.2592	36.598	63	3.5609	0	0	6
13	3.561	5.0028	20.491	63	0	0	0.5488	7
14	3.857	4.3929	20.086	67	0	0	0	7
15	4.055	3.3535	31.187	57	0	0	0.6505	7
16	4.263	4.6646	21.328	66	0	0	0	6
17	4.349	0.657	33.784	70	3.4556	0	0.5488	7
18	4.437	9.8749	38.475	66	0	0	1.4477	6
19	4.759	0.5712	26.311	41	0	0	0	6
20	4.953	1.1972	46.063	70	5.2593	0	0	7
21	5.155	3.1582	30.569	59	0	0	0	6
22	5.259	7.846	33.115	60	4.3492	0	3.8574	7
23	5.474	0.5827	29.371	59	0.4493	0	0	6
24	5.529	5.9299	31.5	63	1.5527	0	3.2544	7
25	5.641	1.477	39.252	69	4.953	0	0	6
26	5.871	4.2631	22.646	68	1.3499	0	0	6
27	6.05	1.6653	41.264	65	0	0	0.4493	7
28	6.172	0.6703	47.942	67	6.1719	0	0	7
29	6.36	2.8292	22.874	67	1.2461	0	1.0513	7
30	6.619	11.134	29.371	65	0	0	5.0531	6
31	6.821	1.3364	59.74	65	7.0993	0	0.4493	6
32	7.463	1.1972	450.339	65	5.4739	0	0	6
33	7.463	3.5966	20.905	71	3.5609	0	0	6
34	7.538	1.0101	26.311	54	0	0	0	6
35	7.768	0.99	25.028	63	0	0	0.4493	6
36	8.085	3.7062	61.559	64	8.7583	0	0	7
37	8.671	4.1371	38.861	73	0.5599	0	5.2593	8
38	8.935	1.5841	10.697	64	0	0	0	7
39	9.116	14.2963	59.74	68	3.9354	1	6.2339	7
40	9.777	2.2255	20.287	56	2.56	0	0.8521	7
41	9.974	1.8589	23.104	60	0	0	0	8
42	10.074	4.2207	39.646	68	0	0	0	7
43	10.278	1.786	47.942	62	5.529	0	0.6505	6
44	10.697	5.8709	49.402	61	0	0	2.2479	7
45	12.429	4.4371	30.265	66	5.7546	0	0.6505	7
46	12.807	5.2593	29.666	61	1.8589	0	0	7
47	13.066	15.3329	54.598	79	6.5535	1	14.2963	8
48	13.066	3.1899	56.826	68	5.529	0	0.6505	7
49	13.33	5.7546	33.115	43	0	0	0	6
50	13.33	3.3872	35.517	70	3.9354	0	0.4493	6
51	14.296	2.9743	54.055	68	0	0	0	7
52	14.585	5.2593	68.717	64	7.9248	0	0	6
53	14.585	1.6653	37.713	64	4.4371	0	1.0513	7
54	14.732	8.4149	61.559	68	5.8709	0	4.2631	7
55	14.88	23.3361	33.784	59	0	0	0	8
56	15.18	3.5609	72.24	66	8.3311	0	0	7
57	16.281	2.6379	17.637	47	0	0	1.6487	7
58	16.281	1.5841	42.948	49	4.1371	0	0	6
59	16.61	1.716	65.366	70	1.5527	0	0	8
60	16.61	2.8864	46.993	61	3.6328	0	0	7
61	17.116	1.5841	91.836	73	10.2779	0	0	6
62	17.288	7.3891	41.264	63	5.0531	1	6.7531	7
63	17.288	16.119	33.784	72	0	0	4.7588	8
64	17.814	7.6141	50.4	66	7.4633	1	8.2482	7
65	17.814	7.9248	37.338	64	0	0	0	6
66	17.993	4.306	46.525	61	3.7434	0	0.6505	7
67	18.541	7.5383	48.424	68	5.9299	0	3.7434	7
68	19.298	9.025	57.397	72	10.0744	0	0.6505	7
69	19.298	0.6376	82.269	69	0	0	0	6
70	19.492	3.2871	119.104	72	10.2779	0	0.4493	7
71	20.287	6.4237	36.234	60	0	1	3.7434	7
72	20.905	3.1899	28.219	77	5.7546	0	0	7
73	21.328	3.3535	46.063	69	0	1	1.2461	7
74	21.758	6.2965	25.534	60	1.5527	1	3.2544	8
75	26.576	20.0855	46.993	69	0	1	6.7531	8
76	28.219	23.1039	26.05	68	0.9512	1	11.2459	6
77	29.666	7.4633	83.931	72	8.3311	0	1.6487	8
78	31.187	12.6797	77.478	78	10.2779	0	0	8
79	31.817	14.154	35.874	69	0	1	13.1971	7
80	33.448	16.119	45.604	63	0	0	1.4477	8
81	33.784	4.3492	21.542	66	1.7507	0	1.2461	7
82	34.124	12.3049	32.137	57	1.5527	0	10.2779	7
83	35.517	13.5991	48.911	77	0.5886	1	1.7507	7
84	35.517	14.5851	46.525	65	3.0649	0	5.7546	8
85	36.234	4.7588	40.854	60	5.4739	0	2.2479	8
86	37.713	27.1126	33.784	64	0	1	10.2779	8
87	39.646	7.5383	41.679	58	5.1552	0	0	6
88	40.854	5.6407	29.079	62	0	1	1.3499	7
89	53.517	16.6099	112.168	65	0	1	11.7048	8
90	54.055	4.7588	40.447	76	2.56	1	2.2479	8
91	56.261	25.7903	60.34	68	0	0	0	6
92	62.178	12.5535	39.646	61	3.8574	1	0	7
93	80.64	16.9455	48.424	68	0	1	3.7434	8
94	107.77	45.6042	49.402	44	0	1	8.7583	8
95	170.716	18.3568	29.964	52	0	1	11.7048	8
96	239.847	17.8143	43.38	68	4.7588	1	4.7588	8
97	265.072	32.1367	52.985	68	1.5527	1	18.1741