Source | SS df MS > Number of obs = 15 -------------+---------------------------------- > F(1, 13) = 1.46 Model | 184.562884 1 184.562884 > Prob > F = 0.2488 Residual | 1646.01046 13 126.616189 > R-squared = 0.1008 -------------+---------------------------------- > Adj R-squared = 0.0317 Total | 1830.57334 14 130.755239 > Root MSE = 11.252

------------------------------------------------ > ------------------------------ medinc | Coef. Std. Err. t > P>|t| > [95% Con > f. Interval] -------------+---------------------------------- > ------------------------------ employ | .5677692 .4702667 1.21 > 0.249 > -.4481803 > 1.583719 _cons | 4.801014 27.21156 0.18 > 0.863 > -53.98598 > 63.58801 ------------------------------------------------ > ------------------------------

3. What percent of variation in the response variable is explained by the explanatory variable? Is this a large amount? 4. How much does your response variable change by when your explanatory variable increases by 5 units? Is this a large change?

5. Is the slope coefficient statistically significant at the 5% significance level? How do you know? 6. Using your regression results, briefly discuss what you have learned about the relationship between the explanatory and response variable and use your intuition to speculate on why this relationship exists.