Regression Diagnostics and Pitfalls The scatterplot below shows fabricated data

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 eamings 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 100 20 12 16 18 20 r: 0.91 Regression Line lot Residuals x-845 y = 4.69 Problem 5 The regression estimate of the price per share of a company whose annual earnings per share is $-26.13 is (Q5) ? because (select all that A: reliable B: unreliable A it is cxtrapolation C the data have outliers D. the data are heteroscedastic apply) (Q6) Enone cf the above

Explanation / Answer

Problem 5: Correct answer: Unreliability

and another Correct answer: A It is extrapolation

since The regressin line of price of share on earning per share is given and displayed in scatter plot

Given the earning per share is given i.e. -26.13 which is not include in this data or the value is not in the X axis.

So it is extrapolation point

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