Using the sample data from the accompanying table, complete parts (a) and (b). E Click the icon to view the data table.
Using the sample data from the accompanying table, complete parts (a) and (b). E Click the icon to view the data table.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Question
![Using the sample data from the accompanying table, complete parts (a) and (b).
E Click the icon to view the data table
(a) Explain why it does not make sense to construct confidence or prediction intervals based on the least-squares regression equation. Choose the correct answer below.
O A. It does not make sense to construct confidence or prediction intervals based on the least-squares regression equation because there is a linear relationship between sugar content and calories in high-protein and moderate protein energy bars.
O B. It does not make sense to construct confidence or prediction intervals based on the least-squares regression equation because there is no linear relationship between sugar content and calories in high-protein and moderate protein energy bars.
O C. It does not make sense to construct confidence or prediction intervals based on the least-squares regression equation because the residuals are not normally distributed.
(b) Construct a 95% confidence interval for the mean sugar content of energy bars.
- X
The 95% confidence interval for the mean sugar content of energy bars is
Data Table
lower bound: upper bound:
(Round to one decimal place as needed.)
Full data set O
Calories, x
Sugar, y
Calories, x
Sugar, y
190
11
270
20
200
19
320
2
210
14
110
10
220
20
180
12
220
200
22
230
28
220
24
240
2
230
24
It can be shown that there is no linear relationship between sugar content and
calories in high-protein and moderate protein energy bars.
Print
Done](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F8ad9f971-b5a4-47c4-8abf-db06412cef63%2Ff7f529c3-758f-486b-86a4-7e24e19ae740%2Fac06dzl_processed.png&w=3840&q=75)
Transcribed Image Text:Using the sample data from the accompanying table, complete parts (a) and (b).
E Click the icon to view the data table
(a) Explain why it does not make sense to construct confidence or prediction intervals based on the least-squares regression equation. Choose the correct answer below.
O A. It does not make sense to construct confidence or prediction intervals based on the least-squares regression equation because there is a linear relationship between sugar content and calories in high-protein and moderate protein energy bars.
O B. It does not make sense to construct confidence or prediction intervals based on the least-squares regression equation because there is no linear relationship between sugar content and calories in high-protein and moderate protein energy bars.
O C. It does not make sense to construct confidence or prediction intervals based on the least-squares regression equation because the residuals are not normally distributed.
(b) Construct a 95% confidence interval for the mean sugar content of energy bars.
- X
The 95% confidence interval for the mean sugar content of energy bars is
Data Table
lower bound: upper bound:
(Round to one decimal place as needed.)
Full data set O
Calories, x
Sugar, y
Calories, x
Sugar, y
190
11
270
20
200
19
320
2
210
14
110
10
220
20
180
12
220
200
22
230
28
220
24
240
2
230
24
It can be shown that there is no linear relationship between sugar content and
calories in high-protein and moderate protein energy bars.
Print
Done
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