1. Greater than or less than

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1. Greater than or less than?
9:44
AA
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O REGRESSION AND CORRELATION
Predictions from the least-squares regression line
SH
A financial analyst is examining the relationship between stock prices
and earnings per share. She chooses fifteen 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 î--0.021 + 0.039x. This line, along with a scatter plot of her data, is shown a
in Figure 1.
Earnings per
share, x
(in dollars)
Current stock
price, y
(in dollars)
30.62
0.89
15.77
0.47
40.14
1.88
51.19
1.61
254
26.79
1.06
18.54
0.74
59.71
2.26
20.78
0.75
38.96
1.16
34.97
1.44
41.67
0.98
42.69
1.43
50
32.30
1.81
58.49
2.74
Figure 1
29.83
1.44
Send data to Excel
Based on her data and her regression line, answer the following:
1. Fill in the blank: For these data, current stock prices that are
greater than the mean of the current stock prices tend to be paired
with values for earnings per share that are the mean of the
values for earnings per share.
Choose one
in earnines
dollars in current stock price?
2. According to the regression equation, for an increase of one dollar
ings per share, there is a corresponding increase of how many L
3. From the regression equation, what is the predicted current stock
price (in dollars) when the earnings per share is 34.97 dollars? (Round U
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 57.34 dollars? (Round|
your answer to at least two decimal places.)
Explanation
Check
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Transcribed Image Text:9:44 AA www-awn.aleks.com O REGRESSION AND CORRELATION Predictions from the least-squares regression line SH A financial analyst is examining the relationship between stock prices and earnings per share. She chooses fifteen 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 î--0.021 + 0.039x. This line, along with a scatter plot of her data, is shown a in Figure 1. Earnings per share, x (in dollars) Current stock price, y (in dollars) 30.62 0.89 15.77 0.47 40.14 1.88 51.19 1.61 254 26.79 1.06 18.54 0.74 59.71 2.26 20.78 0.75 38.96 1.16 34.97 1.44 41.67 0.98 42.69 1.43 50 32.30 1.81 58.49 2.74 Figure 1 29.83 1.44 Send data to Excel Based on her data and her regression line, answer the following: 1. Fill in the blank: For these data, current stock prices that are greater than the mean of the current stock prices tend to be paired with values for earnings per share that are the mean of the values for earnings per share. Choose one in earnines dollars in current stock price? 2. According to the regression equation, for an increase of one dollar ings per share, there is a corresponding increase of how many L 3. From the regression equation, what is the predicted current stock price (in dollars) when the earnings per share is 34.97 dollars? (Round U 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 57.34 dollars? (Round| your answer to at least two decimal places.) Explanation Check 2021 M Errinn A Dinhte Deanun Terms of Use Privaev E 回 国
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