Following table (download in Excel here Download Excel here) shows 100 individual data on health status (score between 0-100), weekly exercise hours, annual income, and diet score (between 0-100). The goal is to explore the relationship between these variables, so that you can predict health score based on all or some of other variables. To achieve this goal: Create scatterplots of health score with each of other variables and interpret the patterns briefly. Analyze the correlation table among the variables. Interpret the correlation matrix. Develop a regression model using all variables and estimate the coefficients using Excel (or other software). Interpret the results, including R square, adjusted R square, and p-values. Based on your conclusion in previous step, develop a new regression model (by removing some of insignificant variables) and compare the R square and p-values of the new model with old model.

HealthScore	Weekly Exercise Hours	Annual Income	Diet Score
56.95744656	5.922138144	6022.3405	24.57055113
63.1890497	9.059590633	62403.5239	45.01586469
60.12666192	8.958010278	10399.85738	40.85669239
33.40811369	9.187411536	2954.973227	43.78644296
19.25277028	6.010914301	49597.18554	24.17543935
23.6593001	15.77708025	27793.57634	17.36885677
5.044399951	19.89290138	39454.31784	22.3292123
64.57581179	9.667003272	39306.62222	35.45054654
48.03473303	17.05654925	52213.01438	35.99771922
3.711303581	18.25503571	19174.43422	22.29589207
19.82442569	7.936227702	35617.96515	17.12696866
66.75291003	19.31133266	34318.86845	38.57416939
95.55842604	15.3203759	56568.14994	39.48042132
28.44134667	3.848724053	32390.52407	6.137087985
26.94642902	3.504115321	40884.36615	17.84114407
80.3859606	7.735379703	87331.84963	6.486786617
31.29665736	8.750682783	35840.72388	64.67918591
52.0822448	7.444424856	55865.92735	57.86674006
48.29453405	0.548545084	68537.96645	44.98884395
76.21099478	6.754485702	65142.77633	5.822607365
47.05185834	1.50642947	32202.47236	1.740094489
45.46947659	10.01238945	25469.42287	59.57638821
41.64394044	15.80258278	10944.96596	19.74244724
95.0135387	12.13972839	68032.39849	32.07216944
64.91996007	16.52404086	45021.51437	17.83636975
75.24703334	1.66922737	2015.775438	28.44459443
93.75616844	8.689508223	69056.09075	12.84808797
75.86271107	0.332483803	30159.41833	68.88529142
96.17594811	4.97736092	30423.91417	42.95593338
72.24781051	11.55392209	27655.70422	63.02731851
12.95820235	11.20939796	11184.22816	1.055178486
13.40798615	7.745740748	28053.6718	13.3107244
53.72233304	7.852853617	2145.56065	7.401807953
49.8206298	5.360972525	51721.86856	10.2588114
36.90554863	9.837331717	17840.00217	21.19078161
28.62068601	14.83153766	38205.08169	23.44452666
90.23686107	4.030423144	86013.05771	86.71965579
83.7731915	19.19340784	63420.27593	89.96187432
36.82604556	8.969205927	17432.77615	59.43352896
81.21040437	5.517215117	4371.646054	26.99879147
2.179030791	8.670839533	1029.010985	29.73380476
90.57353602	5.398880338	79630.9579	3.443813531
6.119450073	1.579788946	35278.01688	8.707485131
32.70555049	18.72849935	12572.50667	39.2420411
19.47874125	6.852093495	34493.50887	28.89486126
83.81890381	10.90241619	10644.50115	72.04104247
83.86354582	15.70893267	60396.13541	73.24397333
82.12066442	19.1607791	63846.08042	85.21829444
0.261427312	0.026576736	30968.24742	12.78805592
77.05052557	4.853682595	55300.16892	30.4924309
85.31640856	1.528998413	32278.85903	32.53786191
63.08895586	8.543516625	13738.44391	6.75539482
37.34512962	9.07142067	1670.077686	15.5816405
42.67985331	19.9754375	7526.179809	47.74093034
19.61601106	18.92147009	18933.9847	6.977898634
76.82037562	19.4260701	904.815174	30.98582294
0.933076095	6.362357406	34397.2	24.35964435
92.62626143	15.9750764	64737.03028	0.22454716
43.00019118	6.362181752	31678.97835	53.28460333
97.63639086	6.935366699	61476.97408	83.13210693
82.2454473	9.572723102	70418.81529	85.76069515
11.62491182	9.476489843	32485.27728	13.67812133
8.574031983	13.74703435	11824.11175	19.86223083
69.35099418	16.97653058	49954.56533	62.77392403
88.84992533	0.569407312	51540.86488	7.05550597
10.1417398	7.947232039	13574.1801	20.62134382
35.65258499	9.188154663	680.1546442	16.40656564
12.40027744	17.39310612	28503.43436	7.856460739
54.09907372	7.02253288	34258.46612	38.22186799
14.68973061	3.53208401	36466.79341	10.32292211
15.72417404	16.42046089	24289.79513	27.34095006
21.86698795	8.740691604	37083.9197	2.869258418
47.71263842	6.789137048	55894.56495	34.34956543
43.76096689	5.776920012	9074.737952	57.2329108
51.33584438	14.2010145	50937.49872	33.78978749
2.330388751	18.32288717	44832.19924	5.126778613
63.19186837	3.68423336	12267.46851	66.98601656
12.1931518	8.50043734	23652.69477	0.73237349
85.32322968	3.610949007	44133.48321	51.68422403
26.79691579	18.03413768	1417.897074	20.78580784
81.43951731	7.511753894	22994.45805	77.63547506
9.81768027	11.65607411	39617.33774	23.92401185
99.79938993	12.09811771	90045.45741	76.54017381
98.09170206	15.61999516	34499.71302	96.97161877
60.89834464	19.20409225	65282.88639	31.92376578
99.47627092	8.506753165	66084.06512	35.2101247
81.38596314	10.97284206	20375.65474	52.1200961
54.06092924	1.993165849	61629.2698	41.30770471
53.08419249	2.576368335	49179.98165	40.04894309
68.11101883	19.15443838	16031.11678	29.83358155
11.96988936	11.8134826	553.4019638	6.190557727
50.84860011	3.733098678	26500.68608	6.9446019
17.24734125	13.38356059	22151.07052	4.968576784
65.9772284	13.50224899	34865.27034	45.8226751
21.51609431	17.08978251	30719.27187	22.81992036
90.16249914	1.408971146	14371.15002	24.68216189
12.8471255	15.35966094	32480.27356	1.287887107
61.89280373	15.02196049	6644.093677	69.01201919
46.53782091	7.567933466	2613.965171	55.15803526
16.07651852	14.58167401	40994.76817	26.31471279