Question: SUMMARY OUTPUT Regression Statistics Multiple R 0.3736 R square 0.1396 Adjusted R Square 0.1217 Standard Error 5824.9199 Observations 50 ANOVA df SS MS F Significance

SUMMARY OUTPUT

Regression Statistics
Multiple R	0.3736
R square	0.1396
Adjusted R Square	0.1217
Standard Error	5824.9199
Observations	50

ANOVA

	df	SS	MS	F	Significance F
Regression	1	264233586.4	264233586.41	7.79	0.008
Residual	48	1628625194	33929691.54
Total	49	1892858780

	Coefficients	Standard Error	t-stat	p-value
Intercept	55536.010004	4824.391094	-2.791	0.008

A public health researcher is interested in examining the economic effects of smoking. Specifically, she has data on two variables measured at the state level: the percentage of residents who smoke (PSMOKE) and annual average wages per capita (ANWAGES). Her hypothesis is that as the percentage of residents who smoke increases, average annual wages decrease. After running a regression (where PSMOKE is the independent variable), she gets the following Excel results attached in the PDF file below.

(1) specifying the regression equation, (2) interpreting the intercept and slope of the equation, (3) explaining the coefficient of determination ( R 2), and (4) testing the statistical significance of the slope of PSMOKE. Based on these information, is there support for the researcher’s hypothesis?

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