A financial analyst is examining the relationship between stock prices and earnings per share. She chooses publicy 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--0.064 + 0.041x. This line, along with a scatter plot of her data, is shown below. Earnings per Current stock price, y (in dollars) 1.41 share, x (in dollars) 28.99 53.10 2.69 43.04 1.57 29.74 O80 24.87 1.10 17.31 58.56 2.16 32.99 1.52 21.47 0.80 38.90 1.36 42.65 1.13 49 83 1.71 13.50 0.48 Earnings per share, (in dollars) 40.86 1.69 58.19 2.72 37.87 1.16 Send data to caliculator v Send data to Ecel Based on the sample data and the regression line, complete the folowing. (a) For these data, current stock prices that are less than the mean of the current stock prices tend to be paired with values for earnings per share that are Choose one) the mean of the values for earnings per share. e) According to the regression equation, for an increase of one dollar in earnings per share, there is a carresponding (Choose one) Vof 0.041 dolars in current stock price. e) From the regression equation, what is the predicted current stock price (in dollars) when the carnings per share is 42.65 dollars? (Round your answer to at least two decimal places.) (4) From the regression equation, what is the predicted current stock price (in dollars) when the earnings per share is 50.32 dollars? (Round your answer to at least two decimal places.) Current stock price, y (Sop u)
A financial analyst is examining the relationship between stock prices and earnings per share. She chooses publicy 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--0.064 + 0.041x. This line, along with a scatter plot of her data, is shown below. Earnings per Current stock price, y (in dollars) 1.41 share, x (in dollars) 28.99 53.10 2.69 43.04 1.57 29.74 O80 24.87 1.10 17.31 58.56 2.16 32.99 1.52 21.47 0.80 38.90 1.36 42.65 1.13 49 83 1.71 13.50 0.48 Earnings per share, (in dollars) 40.86 1.69 58.19 2.72 37.87 1.16 Send data to caliculator v Send data to Ecel Based on the sample data and the regression line, complete the folowing. (a) For these data, current stock prices that are less than the mean of the current stock prices tend to be paired with values for earnings per share that are Choose one) the mean of the values for earnings per share. e) According to the regression equation, for an increase of one dollar in earnings per share, there is a carresponding (Choose one) Vof 0.041 dolars in current stock price. e) From the regression equation, what is the predicted current stock price (in dollars) when the carnings per share is 42.65 dollars? (Round your answer to at least two decimal places.) (4) From the regression equation, what is the predicted current stock price (in dollars) when the earnings per share is 50.32 dollars? (Round your answer to at least two decimal places.) Current stock price, y (Sop u)
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter1: Functions
Section1.EA: Extended Application Using Extrapolation To Predict Life Expectancy
Problem 1EA
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