Question

Year	Revenue	(Entry) # of Companies	Employees	Revenue/Employees
				(Profitability = Y)
2000	$24,996,750,000	39	291,227	85,832.53
2001	$44,745,760,000	63	446,831	100,140.23
2002	$65,444,950,000	87	387,526	168,878.86
2003	$39,937,040,000	85	406,374	98,276.56
2004	$76,985,390,000	102	442,473	173,988.90
2005	$41,571,010,000	98	391,641	106,145.70
2006	$59,540,940,000	104	477,869	124,596.78
2007	$107,513,070,000	127	611,950	175,689.30
2008	$118,890,930,000	145	719,897	165,149.92
2009	$155,165,540,000	160	856,854	181,087.49
2010	$213,437,520,000	144	916,889	232,784.47
2011	$159,266,760,000	122	773,126	206,003.63
2012	$94,751,110,000	54	499,211	189,801.73
2013	$85,184,260,000	35	498,395	170,917.16
2014	$113,949,560,000	49	573,167	198,806.91
2015	$127,059,310,000	65	781,837	162,513.81
2016	$130,005,490,000	81	813,389	159,831.88
2017	$129,021,400,000	59	647,861	199,149.82
2018	$145,397,350,000	59	748,140	194,345.11

Do new entrants and employees affect the Healthcare industry for the years 2000-2018?

Dependent variable - industry's revenue

Independent variable - the number of new entrants and employees + omitted variables

Using the above table create:

- Hypothesis testing

- P-value

- T-test

- Level of significance

- Scatter Plot

- Regression analysis

Answer 1

year	revenue ($)	new entrants	employees
2000	24,996,750,000	39	291,227
2001	44,745,760,000	63	446,831
2002	65,444,950,000	87	387,526
2003	39,937,040,000	85	406,374
2004	76,985,390,000	102	442,473
2005	41,571,010,000	98	391,641
2006	59,540,940,000	104	477,869
2007	107,513,070,000	127	611,950
2008	118,890,930,000	145	719,897
2009	155,165,540,000	160	856,854
2010	213,437,520,000	144	916,889
2011	159,266,760,000	122	773,126
2012	94,751,110,000	54	499,211
2013	85,184,260,000	35	498,395
2014	113,949,560,000	49	573,167
2015	127,059,310,000	65	781,837
2016	130,005,490,000	81	813,389
2017	129,021,400,000	59	647,861
2018	145,397,350,000	59	748,140

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.94
R Square	0.89
Adjusted R Square	0.88
Standard Error	17308106003
Observations	19
ANOVA
	df	SS	MS	F	Significance F
Regression	2	3.9E+22	1.95E+22	65.135	2.04977E-08
Residual	16	4.79E+21	3E+20
Total	18	4.38E+22
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	-46503995841	1.41E+10	-3.29029	0.005	-76466103968	-1.7E+10	-7.6E+10	-1.7E+10
new entrants	-30193174.51	1.24E+08	-0.24342	0.811	-293136475.1	2.33E+08	-2.9E+08	2.33E+08
employees	254071.0106	25217.6	10.07515	0.000	200612.0913	307529.9	200612.1	307529.9

new entrants in the industry and employyes in the industry explain 94% of variation in the industry revenue

variable	t-statistic	p-value
new entrants	-0.243	0.811
employees	10.75	0.000

out of the 2 independent variables, new entrants variable is not statistically significant both at 5% & 1% level of significance as p-value is greater than 0.01 & 0.05

employees variable is statistically significant at both 1% & 5% level of significance as p-value is less than 0.01 and 0.05

Scatter plot shows a strong positive relationship between number of employees and revenue of industry

scatter plot shows a weak relaltionship between number of employees and revenue of industry

This is further shown by the correlation matrix

	revenue ($)	new entrants	employees	revenue/employees
revenue ($)	1
new entrants	0.443	1
employees	0.943	0.488	1
revenue/employees	0.868	0.255	0.693	1