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Analyzing Stock Based on EPS

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A financial analyst is examining the relationship between stock prices and earnings per share. She chooses sixteen publicly traded companies at random and records for each the company's current stock price and the company's earnings per share reported for the past 12 months. Her data are given below, with x denoting the earnings per share from the previous year, and y denoting the current stock price (both in dollars). Based on these data, she computes the least-squares regression line to be ^y=0.186 + 0.045x

Earnings per Current stock price
share, x (in dollars) y, (in dollars)
30.83 1.69
29.56 1.4
59 2.31
30.46 0.9
14.01 0.52
25.47 1.11
17.41 0.67
58.37 2.9
37.62 1.36
21.31 0.52
41.84 1.11
50.47 1.49
41.93 1.63
37.79 1.33
52.25 2.69
40.48 1.74

For these data, values for earnings per share that are less than the mean of the values for earnings per share tend to be paired with current stock prices that are greater than or less than the mean of the current stock prices?
According to the regression equation, for an increase of one dollar in earnings per share, there is a corresponding increase of how many dollars in current stock price?
What was the observed current stock price (in dollars) when the earnings per share was 30.83 dollars?

From the regression equation, what is the predicted current stock price (in dollars) when the earnings per share is 30.83 dollars? (Round your answer to at least two decimal places)

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Solution Summary

Just over 100 words explain how to find the predicted current stock price from a regression equation.

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(i) Since the slope of the regression is positive, we can say that the values for earnings per share that are less than the mean of the values for ...

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