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Suppose You Regress the Number of Days That Individuals Report

question 44

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Suppose you regress the number of days that individuals report having hunted in the past year on years of education and that you get the results in Figure 4.3. SUMMARY OUTPUT

 Regression Statistics  Multiple R 0.069296763 R Square 0.004802041 Adjusted R Square 0.004749178 Standard Error 9.950755489 Observations 18828\begin{array}{lc}\hline \text { Regression Statistics } & \\\hline \text { Multiple R } & 0.069296763 \\\text { R Square } & 0.004802041 \\\text { Adjusted R Square } & 0.004749178 \\\text { Standard Error } & 9.950755489 \\\text { Observations } & 18828 \\\hline\end{array}

 ANOVA dfSSMSF Significance F Regression 18994.6978538994.69785390.839444461.74217E21 Residual 188261864104.1199.0175348 Total 188271873098.808\begin{array}{l}\text { ANOVA }\\\begin{array}{lccccc}\hline & d f & S S & M S & F & \text { Significance } F \\\hline \text { Regression } & 1 & 8994.697853 & 8994.697853 & 90.83944446 & 1.74217 \mathrm{E}-21 \\\text { Residual } & 18826 & 1864104.11 & 99.0175348 & & \\\text { Total } & 18827 & 1873098.808 & & & \\\hline\end{array}\end{array}

 Caefficients  Standard Error t Stat  P-value  Lower 95% Upper 95% Intercept 6.87990.432015.92600.00006.03317.7266 Years of Education 0.29690.03129.53100.00000.35800.2358\begin{array}{lcccccc}\hline & \text { Caefficients } & \text { Standard Error } & t \text { Stat } & \text { P-value } & \text { Lower } 95 \% & \text { Upper } 95 \% \\\hline \text { Intercept } & 6.8799 & 0.4320 & 15.9260 & 0.0000 & 6.0331 & 7.7266 \\\text { Years of Education } & -0.2969 & 0.0312 & -9.5310 & 0.0000 & -0.3580 & -0.2358 \\\hline\end{array}
Figure 4.34.3
How would you interpret these results? What would you say about the Goodness-of-Fit of the regression? Explain.

What would be the predicted number of hunting days for an individual with 12 years of education? 16 years of education? Show your work.


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