Regression Statistics
Multiple R	0.70995212
R Square	0.50403202
Adjusted R Square	0.50086627
Standard Error	12063.8519
Observations	474
ANOVA
	df	SS	MS	F	Significance F
Regression	3	6.9514E+10	2.3171E+10	159.21394	3.3298E-71
Residual	470	6.8402E+10	145536523
Total	473	1.3792E+11
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	-13313.269	2763.35782	-4.8177869	1.9618E-06	-18743.334	-7883.2043	-18743.334	-7883.2043
gender	9022.21202	1201.22739	7.51082778	2.9827E-13	6661.77117	11382.6529	6661.77117	11382.6529
minority	-5116.84	1362.97752	-3.7541631	0.00019571	-7795.1237	-2438.5562	-7795.1237	-2438.5562
education	3257.19864	208.853422	15.5956201	1.708E-44	2846.79661	3667.60066	2846.79661	3667.60066

1. A measure on how well the independent variables gender, minority, and education are able to explain the variation in average salary is the adjusted R Squared. What percentage of the variation in average salaries is described by these variables?
2. The t Stat is a measure of how an individual independent variable explains variation in the dependent variable average salary. An absolute value greater than 2 is generally considered a significant value in explaining variation. What do the t Stats tell us about the ability of the variables gender, minority, and education to explain average salary?