accompanying data represent the total compensation for 12

randomly selected chief executive officers_ (CEOs) and the_

company’s stock performance. Use the data to complete parts_ (a)

through_ (d). beta 0_0 and beta 1_1. The estimate of beta 1_1 is?

_(Round to three decimal places as_ needed.) Data Table of

Compensation and Stock Performance Company Compensation _(millions

of_ dollars) Stock Return_ (%) A 15.98 77.34 B 4.17 67.65 C 6.18

140.24 D 1.16 32.11 E 1.85 10.43 F 2.24 29.52 G 11.24 0.65 H 7.09

66.46 I 8.91 59.09 J 3.15 54.84 K 20.97 22.89 L 6.15 31.77 _(a)

Treating compensation as the explanatory_ variable, x, use

technology to determine the estimates of beta 0_0 and beta 1_1. The

estimate of beta 1_1 is _(Round to three decimal places as_

needed.) The estimate of beta 0_0 is _(Round to one decimal place

as_ needed.) _(b) Assuming that the residuals are normally

distributed_, test whether a linear relation exists between

compensation and stock return at the alpha_equals= level of

significance. What are the null and alternative_ hypotheses? A.

Upper H 0H0_: beta 1_1equals=0 Upper H 1H1_: beta 1_1not equals_0

B. Upper H 0H0_: beta 0_0not equals_0 Upper H 1H1_: beta

0_0equals=0 C. Upper H 0H0_: beta 0_0equals=0 Upper H 1H1_: beta

0_0not equals_0 D. Upper H 0H0_: beta 1_1not equals_0 Upper H 1H1_:

beta 1_1equals=0 Compute the test statistic using technology.

_(Round to two decimal places as_ needed.) Compute the_ P-value

using technology.? _(Round to three decimal places as_ needed.)

State the appropriate conclusion. Choose the correct answer below.

A.Do not reject Upper H 0H0. There is sufficient evidence to

conclude that a linear relation exists between compensation and

stock return. B.Reject Upper H 0H0. There is not sufficient

evidence to conclude that a linear relation exists between

compensation and stock return. C.Reject Upper H 0H0. There is

sufficient evidence to conclude that a linear relation exists

between compensation and stock return. D.Do not reject Upper H 0H0.

There is not sufficient evidence to conclude that a linear relation

exists between compensation and stock return.Your answer is

correct._(c) Assuming the residuals are normally_ distributed,

construct a 95% confidence interval for the slope of the true_

least-squares regression line. Lower bound equals= Upper bound

equals= _ (Round to two decimal places as_ needed.) _(d) Based on

your results to parts_ (b) and_ (c), would you recommend using the_

least-squares regression line to predict the stock return of a

company based on the_CEO’s compensation?_ Why? What would be a good

estimate of the stock return based on the data in the_ table? A.

Based on the results from parts_ (b) and_ (c), the regression line

should not be used to predict the stock return. The mean stock

return would be a good estimate of the stock return based on the

data in the table. Based on the results from parts_ (b), the

regression line should not be used to predict the stock return._

However, the results from part_ (c) indicate that the regression

line should be used. The results are not conclusive and further

analysis of the data is needed. C. Based on the results from parts_

(b), the regression line could be used to predict the stock

return._ However, the results from part_ (b) indicate that the

regression line should not be used. The results are not conclusive

and further analysis of the data is needed. D. The regression line

could be used to predict the stock return. The test in part_ (b)

and the confidence interval in part_ (c) both confirm that there is

a relationship between the variables.

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