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Suppose You Regress the Number of Days That Individuals Report

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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 5.3. SUMMARY OUTPUT

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

 ANOVA dfSS MS F 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 & \text { MS } & 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}

 Coefficients  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 { Coefficients } & \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 5.3\text { Figure } 5.3
What would you conclude about the statistical significance of the estimated sample regression function? The estimated intercept? The estimated slope coefficient? Explain.

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Because .0511 > .05 you would conclude t...

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