12. Run a regression of earnings over height (earnings is the dependent/y variable). height 90 80 70 ....." ......9858585659595......"Y = 28 05x+ 66:249- y= 2E-05x + 66.243 60 50 40 30 20 10 100 00 20000 30000 400 00 50000 600 00 700 00 800 00 900 00 13. What is the predicted intercept? -532.9207922 14. What is the predicted slope? 707.9407922 15. What is the effect of height on earnings? (you should read/report the slope, the slope is the effect of x variable on y, 1 unit of x causes B1 unit of y). Increase by 1 inch in height causes increase by 707.9407922 16. Write down the predicted equation. (you can use excel for this and add the trend line). Y=2E-05x+66.243 17. What is the predicted value of earnings for someone who is 68 inches tall? (in your predicted equation insert 68 for height/x and calculate earnings/y) x=68, y = 47607.05304 18. What is r-squared of the regression? Is our regression a good fit? r^2= 0.010884588 19. Is the B1 significant? Why or why not? 20. What is the confidence interval for B1? What does this interval mean