The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $2 million. Is the result close to the actual number of viewers, 5.1 million? Use a significance level of 0.05. Salary (millions of $) Viewers (millions) 101 8 8 3 12 12 8 9 5.5 7.4 6.8 4.7 5.6 6.6 2.3 9.1 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=+x (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $2 million? The best predicted number of viewers for a television star with a salary of $2 million is million. (Round to one decimal place as needed.) Is the result close to the actual number of viewers, 5.1 million? O A. The result is exactly the same as the actual number of viewers of 5.1 million. O B. The result is not very close to the actual number of viewers of 5.1 million. OC. The result is very close to the actual number of viewers of 5.1 million. O D. The result does not make sense given the context of the data.

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The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $2 million. Is
the result close to the actual number of viewers, 5.1 million? Use a significance level of 0.05.
101
Salary (millions of $)
Viewers (millions)
8
8
3
12
12
8
9
5.5
7.4
6.8
4.7
5.6
6.6
2.3
9.1
Click the icon to view the critical values of the Pearson correlation coefficient r.
What is the regression equation?
y = + x (Round to three decimal places as needed.)
What is the best predicted number of viewers for a television star with a salary of $2 million?
The best predicted number of viewers for a television star with a salary of $2 million is
million.
(Round to one decimal place as needed.)
Is the result close to the actual number of viewers, 5.1 million?
O A. The result is exactly the same as the actual number of viewers of 5.1 million.
O B. The result is not very close to the actual number of viewers of 5.1 million.
O C. The result is very close to the actual number of viewers of 5.1 million.
O D. The result does not make sense given the context of the data.
Transcribed Image Text:The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $2 million. Is the result close to the actual number of viewers, 5.1 million? Use a significance level of 0.05. 101 Salary (millions of $) Viewers (millions) 8 8 3 12 12 8 9 5.5 7.4 6.8 4.7 5.6 6.6 2.3 9.1 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y = + x (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $2 million? The best predicted number of viewers for a television star with a salary of $2 million is million. (Round to one decimal place as needed.) Is the result close to the actual number of viewers, 5.1 million? O A. The result is exactly the same as the actual number of viewers of 5.1 million. O B. The result is not very close to the actual number of viewers of 5.1 million. O C. The result is very close to the actual number of viewers of 5.1 million. O D. The result does not make sense given the context of the data.
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