1) Data 4-12 has cross section data for 50 states and Washington D.C. for mortality rates and their determinants. The Y variable is MORT (Total Mortality rate per 100,000 population).

The explanatory variables are:

INCC = per capita income by state in dollars

POV = proportion of families living below the poverty level

EDU1 = proportion of population completing four years of high school.EDU2 = proportion of population completing four years or more of college.

ALCC = Per-capita consumption of alcohol in gallons.

TOBC = per-capita consumption of cigarettes in packs.

HEXC = healthcare expenditures per capita in $.PHYS= physicians per 100,000 population.

URB = proportion of population living in urban areas.

AGED = Proportion of population over the age of 65.

Do not include in the regression variables that are not in this list.

a) For each explanatory variable, explain why it might have a causal effect on mortality (explain why it is + or -).

b) Run the regression model. Do the signs of the coefficients coincide with your intuition? Identify the ones that do not.

c) Which variables are statistically significant at the 5% level?

d) What other variables can you think of that might be an explanatory variable in the model?

DATA 4-12

MORT	INCC	POV	EDU1	EDU2	ALCC	TOBC	HEXC	PHYS	URB	AGED
934.9	10673	0.189	0.565	0.122	1.9	114.5	1620	142	0.675	0.122
396.2	18187	0.107	0.825	0.211	3.86	128.9	1667	127	0.417	0.034
771.5	12795	0.132	0.724	0.174	3.08	107.1	1473	184	0.764	0.123
1022.8	10476	0.19	0.555	0.108	1.78	125.8	1552	136	0.397	0.149
766	16065	0.114	0.735	0.196	3.19	102.8	2069	235	0.957	0.106
625.7	14812	0.101	0.786	0.23	3.09	112.4	1664	196	0.817	0.09
888.4	18089	0.08	0.703	0.207	2.8	111	1945	275	0.926	0.133
880.2	14272	0.119	0.686	0.175	3.17	144.5	1691	185	0.659	0.114
1120.5	18168	0.186	0.671	0.275	5.34	122.1	3872	552	1	0.122
1065.6	13742	0.135	0.667	0.149	3.12	124.2	1886	191	0.908	0.177
814.3	12543	0.166	0.564	0.146	2.48	128.8	1755	159	0.648	0.1
554.2	13814	0.099	0.738	0.203	2.97	69.8	1693	212	0.763	0.097
708.7	11120	0.126	0.737	0.158	2.43	100.7	1288	118	0.2	0.112
886.5	14738	0.11	0.665	0.162	2.77	121.6	1864	199	0.825	0.12
876.3	12446	0.097	0.664	0.125	2.19	135.3	1625	142	0.681	0.119
966.1	12594	0.101	0.715	0.139	2.09	109.4	1758	136	0.434	0.145
900.3	13775	0.101	0.733	0.17	1.95	115.7	1820	162	0.534	0.134
935	10824	0.176	0.531	0.111	1.85	182.4	1404	149	0.461	0.12
825.4	11274	0.186	0.577	0.139	2.63	125	1716	173	0.692	0.101
979.4	11887	0.13	0.687	0.144	2.57	127.9	1641	165	0.361	0.133
833.6	15864	0.098	0.674	0.204	2.84	121.9	1732	303	0.929	0.106
955.4	16380	0.096	0.722	0.2	3.04	117.2	2289	300	0.906	0.136
866.2	13608	0.104	0.68	0.143	2.6	126.6	1996	174	0.799	0.114
830.2	14087	0.095	0.731	0.174	2.68	113	1888	203	0.666	0.125
944.6	9187	0.239	0.548	0.123	2.06	115.3	1519	117	0.305	0.12
1000.4	13244	0.122	0.635	0.139	2.27	129.2	1858	179	0.66	0.137
815	10974	0.123	0.744	0.175	2.95	103.6	1494	136	0.242	0.121
928.5	13281	0.107	0.734	0.155	2.41	105.1	1766	156	0.476	0.136
772.3	14488	0.087	0.755	0.144	5.19	146.7	1946	155	0.826	0.103
849.1	14964	0.085	0.723	0.182	4.91	201.1	1417	179	0.563	0.116
940.7	17211	0.095	0.674	0.183	2.83	116.9	1702	219	1	0.129
672.8	10914	0.176	0.689	0.176	2.75	88	1385	161	0.489	0.098
969.9	16050	0.134	0.663	0.179	2.67	115.9	2412	287	0.912	0.128
846.3	11617	0.148	0.548	0.132	2.13	156.3	1380	168	0.554	0.115
821.6	12052	0.126	0.664	0.148	2.55	103.2	1872	157	0.384	0.13
920.6	13228	0.103	0.67	0.137	2.26	126.7	1833	182	0.789	0.123
900.8	12232	0.134	0.66	0.151	1.91	124.2	1644	138	0.588	0.124
889.7	12622	0.107	0.756	0.179	2.63	118.6	1654	189	0.677	0.134
1043.9	13437	0.105	0.647	0.136	2.25	115.8	1894	214	0.848	0.146
997.6	13906	0.103	0.611	0.154	2.92	133.4	2054	223	0.926	0.146
812.6	10586	0.166	0.537	0.134	2.5	125.4	1341	146	0.605	0.105
932.6	11161	0.169	0.679	0.14	2.33	104.4	1617	130	0.291	0.139
906.8	11243	0.165	0.562	0.126	1.95	128.7	1671	176	0.671	0.123
722.2	13483	0.147	0.626	0.169	2.82	115.9	1577	160	0.813	0.095
550.1	10493	0.103	0.8	0.199	1.53	66.5	1203	171	0.774	0.08
871.4	12117	0.121	0.71	0.19	3.12	144.5	1481	232	0.232	0.119
794.1	14542	0.118	0.624	0.191	2.55	134.6	1498	194	0.722	0.105
782.8	13876	0.098	0.776	0.19	2.71	96.5	1660	196	0.816	0.117
1003.8	10193	0.15	0.56	0.104	1.68	109.1	1542	156	0.365	0.136
868.8	13154	0.087	0.696	0.148	3.19	107	1862	172	0.665	0.13
642.9	13223	0.079	0.779	0.172	2.86	125.7	1453	125	0.292	0.084

2) Data 4-13 has data on factors affecting baseball attendance in 78 metropolitan areas, complied by Scott Daniel. The Y variable is ATTEND (Total Attendance 1984-1986, in thousands). The explanatory variables are:

POP = population of the metropolitan area.

CAPACITY = capacity of the home stadium in thousands.

PRIORWIN = # of wins the team had in the previous season.

CURNTWIN = # of wins the team had in the previous season.GF = # of games behind the division leader the team is after the season was over.

OTHER = # of other baseball teams in the metropolitan area.

TEAMS = the number of football, basketball, or hockey teams found in the metropolitan area.

Do not include in the regression variables that are not in this list.

a) For each explanatory variable, explain why it might have a causal effect on ATTEND. Make sure you identify if it is positive or negative (explain why it is + or -).

b) Run the regression model. Do the signs of the coefficients coincide with your intuition? Identify the ones that do not.

c) Which variables are statistically significant at the 5% level?

d) What other variables can you think of that might be an explanatory variable in the model?

DATA 4-13

ATTEND	POP	CAPACITY	PRIORWIN	CURNTWIN	G1	G2	G3	G4	G5	GF	OTHER	TEAMS
2704.794	4353	52.806	92	104	0	0	0	0	0	0	0	3
2110.009	2803	43.737	89	89	6	5.5	10	12	9.5	15	0	2
1821.815	9120	57.545	91	87	10.5	17.5	21	20	15	17	1	7
1661.618	2763	33.583	84	86	10	16.5	19	16.5	15.5	18	0	2
2045.784	2174	53.197	98	85	9.5	10.5	13.5	14.5	14	19	0	1
734.079	1899	74.208	70	75	7.5	19.5	22.5	26	27.5	29	0	2
1608.509	1397	53.192	87	67	9	15	21	25	31	36.5	0	1
2468.925	2803	43.737	89	99	0	0	0	0	0	0	0	2
2214.587	9120	57.545	87	97	6	5.5	7.5	7.5	5	2	1	7
2286.609	4353	52.806	104	84	1	5.5	3.5	9.5	11.5	15	0	3
2132.387	2174	53.198	85	83	0.5	4	7.5	12.5	12.5	16	0	1
1786.633	2763	33.583	86	81	4	9.5	7.5	10.5	20.5	18.5	0	2
1360.265	1397	53.192	67	71	4.5	8	11	18	20.5	28	0	1
655.181	1899	74.208	75	60	6	14.5	22	31	35	39.5	0	2
2147.641	2763	33.583	81	95	2.5	0	0	0	0	0	0	2
2268.03	9120	57.545	97	90	0	2.5	8	4	6.5	5.5	1	6
1899.437	4353	52.806	84	87	3.5	8	12	6	9	8.5	0	3
2455.477	2803	43.737	99	86	5	10	10.5	5.5	3.5	9.5	0	2
1471.805	1899	74.208	60	84	2.5	9	10.5	6	11.5	11.5	0	2
1265.041	1397	53.192	71	77	4	7.5	12	9.5	11.5	18	0	1
1973.176	2174	54.076	83	73	4	3.5	10	4.5	11	22.5	0	1
1810.018	1327	40.625	79	84	3.5	3.5	5.5	5	2	0	0	2
2402.997	1932	65.158	70	81	0	0	0	1.5	2.5	3	0	1
1598.692	2114	55.122	70	81	3	1	3	0	0	3	0	2
1353.281	3253	50.219	74	77	1	2.5	3.5	8	12.5	7	1	2
2136.988	7102	44.432	99	74	4.5	2.5	3	4.5	6.5	10	1	3
870.372	1607	59.438	60	74	1.5	2.5	4.5	7	10.5	10	0	2
1102.471	2975	43.508	77	69	5	5	6.5	10.5	9	14.5	0	2
2162.171	1327	40.625	84	91	2	1	3.5	2.5	2.5	0	0	1
2567.427	1932	65.158	81	90	0	0	0	0	0	1	0	1
1699.888	7102	44.432	74	85	3	2.5	4.5	3.5	9	6	1	3
1615.814	2114	55.122	81	77	2.5	5	7	10.5	14	14	0	2
1334.599	3253	50.255	77	77	5	4	2	5	6	14	1	2
1128.696	1607	59.438	74	74	5	6	5	9.5	14	17	0	2
1112.497	2975	43.508	69	62	6	9	13.5	18.5	24.5	28.5	0	2
2655.872	1932	64.573	90	92	0	1.5	0	0	0	0	0	1
1692.002	2975	43.508	62	87	3	0	0.5	3.5	5.5	5	0	2
2320.794	1327	40.625	91	76	3	1	3.5	9.5	14	16	0	1
1314.646	3253	50.219	77	76	2	2	11.5	12.5	14	16	1	2
1424.313	7102	44.087	85	72	5	5.5	6.5	10.5	17.5	20	1	3
1255.453	2114	55.244	77	71	5	5.5	7	12	19	21	0	2
1029.045	1607	59.438	74	67	6	7	9.5	11	17	25	0	2
1983.904	1862	58.671	81	92	1	0.5	0	0	0	0	0	1
1724.892	2030	53.046	88	80	6	1	2.5	8.5	12	12	0	2
1229.862	2905	45	85	80	7.5	6.5	8.5	14	10.5	12	0	2
3134.824	7478	56	91	79	0	0	5.5	12	15.5	13	0	4
1275.887	1401	52.392	74	70	6	1	9.5	19	23.5	22	0	1
1001.545	3253	58	79	66	9	9	14	21.5	22	26	1	2
3264.593	7478	56	79	95	0	5	4.5	0	0	0	0	4
1834.619	1401	52.392	70	89	0.5	3.5	3.5	5.5	7.5	5.5	0	1
1184.314	2905	45	80	83	0.5	3.5	6	13	14.5	12	0	2
2210.352	1862	58.671	92	83	0	0	0	5	7	12	0	1
1350.137	2030	53.046	80	66	1	8	10	14	19.5	29	0	2
818.697	3253	58	66	62	3	10	17	19.5	23.5	33	1	2
1734.276	2905	45	83	96	0	0	0	0	0	0	0	2
1692.432	1401	52.392	89	86	7.5	8	8	8.5	7	10	0	1
1528.748	3253	58	62	83	1.5	3	0.5	4	8	13	1	2
1805.716	1862	58.402	83	74	2.5	3.5	3	6.5	12.5	22	0	1
3023.208	7478	56	95	73	5.5	5.5	7.5	7.5	11	23	0	4
1387.181	2030	53.046	66	72	6.5	2.5	2	10.5	11.5	23.5	0	2
2104.219	7102	37.242	71	96	0	0.5	0	0	0	0	1	3
1842.695	9120	55.601	68	90	0	3.5	2.5	1.5	5.5	6.5	1	7
2037.448	2355	50.1	79	84	2.5	5.5	5	8.5	12	12.5	0	2
2062.693	4717	65.454	90	81	1	0	0	3.5	8.5	15.5	0	3
1606.531	2802	59.149	82	78	1	4	4.5	8.5	13.5	18	0	2
773.5	2264	58.365	84	75	5	7.5	12	16	22	21.5	0	2
2637.563	2355	50.1	84	101	4.5	4	0	0	0	0	0	2
2761.601	9120	55.3	90	98	0	0	5	2	2	3	1	7
1502.494	2802	59.149	78	84	1	2	1.5	6	7	16.5	0	2
2161.534	7102	37.272	96	77	0	0.5	4	8.5	15.5	23.5	1	3
1830.35	4717	66.744	81	75	4.5	11	11	15.5	16.5	26	0	3
735.9	2264	58.429	75	57	6	12.5	18.5	28	37	43.5	0	2
2767.601	9120	55.3	98	108	0	0	0	0	0	0	1	6
1933.335	4717	66.271	75	86	5.5	11.5	15.5	17.5	19	21.5	0	3
2471.974	2355	50.1	101	79	6	14.5	19	20.5	22	28.5	0	2
1128.981	2802	59.149	84	78	5	6	9.5	15.5	23.5	29.5	0	2
1859.102	7102	38.04	77	70	7.5	13.5	22	22.5	32	37	1	3
1000.917	2264	58.438	57	64	6.5	13	21	25	34	44	0	2