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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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