What is the regression equation? ý=D•4× (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $15 million? The best predicted number of viewers for a television star with a salary of $15 million is O million. (Round to one decimal place as needed.) Is the result close to the actual number of viewers, 9.0 million? O A. The result is very close to the actual number of viewers of 9.0 million. O B. The result is exactly the same as the actual number of viewers of 9.0 million. OC. The result is not very close to the actual number of viewers of 9.0 million. O D. The result does not make sense given the context of the data.
What is the regression equation? ý=D•4× (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $15 million? The best predicted number of viewers for a television star with a salary of $15 million is O million. (Round to one decimal place as needed.) Is the result close to the actual number of viewers, 9.0 million? O A. The result is very close to the actual number of viewers of 9.0 million. O B. The result is exactly the same as the actual number of viewers of 9.0 million. OC. The result is not very close to the actual number of viewers of 9.0 million. O D. The result does not make sense given the context of the data.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
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
$15
million. Is the result close to the actual number of viewers,
9.0
million? Use a significance level of 0.05.|
Salary (millions of $)
|
118
|
13
|
4
|
11
|
9
|
6
|
8
|
9
|
|
|---|---|---|---|---|---|---|---|---|---|
|
Viewers (millions)
|
10.7
|
1.3
|
10.2
|
10.9
|
3.2
|
2.5
|
7.2
|
4.3
|
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What is the regression equation?
y=enter your response here+44x
(Round to three decimal places as needed.)What is the best predicted number of viewers for a television star with a salary of
$15
million?The best predicted number of viewers for a television star with a salary of
$15
million is
enter your response here
million.(Round to one decimal place as needed.)
Is the result close to the actual number of viewers,
9.0
million?The result is very close to the actual number of viewers of
9.0
million.The result is exactly the same as the actual number of viewers of
9.0
million.The result is not very close to the actual number of viewers of
9.0
million.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 $15 million. Is the
result close to the actual number of viewers, 9.0 million? Use a significance level of 0.05.
Salary (millions of $)
Viewers (millions)
118
13
4
11
9.
6
8
9.
10.7
1.3
10.2
10.9
3.2
2.5
7.2
4.3
Click the icon to view the critical values of the Pearson correlation coefficient r.
.....
What is the regression equation?
y =| + 4 x (Round to three decimal places as needed.)
%3D
What is the best predicted number of viewers for a television star with a salary of $15 million?
The best predicted number of viewers for a television star with a salary of $15 million is
million.
(Round to one decimal place as needed.)
Is the result close to the actual number of viewers, 9.0 million?
A. The result is very close to the actual number of viewers of 9.0 million.
B. The result is exactly the same as the actual number of viewers of 9.0 million.
C. The result is not very close to the actual number of viewers of 9.0 million.
D. The result does not make sense given the context of the data.
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