Regression Diagnostics and Pitfalls The scatterplot below shows fabricated data
ID: 3045725 • Letter: R
Question
Regression Diagnostics and Pitfalls The scatterplot below shows fabricated data for the price per share versus earnings per share per year of 100 public corporations. The average earnings per share is $9.75 per year with an SD of $5.98 per year, and the average price per share is $69.23 with an SD of $34.81. The correlation between price and earnings is 0.905. (Use this figure in your calculations, not the value of the correlation coefficient in the applet.) Faux Price per share vs. Earnings Data 140 120 100- 60 0 10 12 16 18 r: 0.91 Regression Line Plot Residuals x-8.45 y 4.69 Problem 7 The ms error of regression for regressing price against earnings is (Q9) (010) 2 A no units) C: $ per year D years per $ E: per year F: per $Explanation / Answer
se^2 = sy^2 (1-r^2) (n-1)/(n-2)
here n = 100 ,
r = 0.905, sy = 34.81
se ^2 = 34.81^2 * (1 - 0.905^2 ) * 99/98 = 221.53163397
se = sqrt(221.53163397) = 14.88393
Q10
unit - dollar per year