11.7. Machine speed. The number of defective items produced by a machine (Y) is known to be linearly related to the speed setting of the machine (X). The data below were collected from recent quality control records. i: 1 2 3 4 56 7 8 9 10 11 12 Xi: 200 400 300 400 200 300 300 400 200 400 200 300 Yi: 40 28 75 37 53 22 52 30 58 96 46 69
11.7. Machine speed. The number of defective items produced by a machine (Y) is known to be linearly related to the speed setting of the machine (X). The data below were collected from recent quality control records. i: 1 2 3 4 56 7 8 9 10 11 12 Xi: 200 400 300 400 200 300 300 400 200 400 200 300 Yi: 40 28 75 37 53 22 52 30 58 96 46 69
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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Please give handwritten
![11.7. Machine speed. The number of defective
items produced by a machine (Y) is known to
be linearly related to the speed setting of the
machine (X). The data below were collected
from recent quality control records.
i: 1 2 3 4 5 6 7 8 9 10 11 12
Xi: 200 400 300 400 200 300 300
400 200 400 200 300
Yi:
40
28
96
75
46
37
52
53
30
22
69
58
a. Fit a linear regression function by ordinary
least squares, obtain the residuals, and plot
the residuals against X. What does the
residual plot suggest?
b. Conduct the Breusch-Pagan test for
constancy of the error variance, assuming
loge oi2 = yo + y1 Xi; use a = .10. State the
alternatives, decision rule, and conclusion.
c. Plot the squared residuals against X. What
does the plot suggest about the relation
between the variance of the error term and X?](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fe108db35-1e44-429b-b51d-843cba6d4095%2Fc5522d76-ada6-466a-b87b-0dd92ecbc277%2F5d5vq4c_processed.jpeg&w=3840&q=75)
Transcribed Image Text:11.7. Machine speed. The number of defective
items produced by a machine (Y) is known to
be linearly related to the speed setting of the
machine (X). The data below were collected
from recent quality control records.
i: 1 2 3 4 5 6 7 8 9 10 11 12
Xi: 200 400 300 400 200 300 300
400 200 400 200 300
Yi:
40
28
96
75
46
37
52
53
30
22
69
58
a. Fit a linear regression function by ordinary
least squares, obtain the residuals, and plot
the residuals against X. What does the
residual plot suggest?
b. Conduct the Breusch-Pagan test for
constancy of the error variance, assuming
loge oi2 = yo + y1 Xi; use a = .10. State the
alternatives, decision rule, and conclusion.
c. Plot the squared residuals against X. What
does the plot suggest about the relation
between the variance of the error term and X?
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