An experiment analyzes imperfection rates for two processes used to fabricate silicon wafers for computer chips. For treatment A applied to 10 wafers, the numbers of imperfections are 8, 7, 6, 6, 3, 4, 7, 2, 3, 4. Treatment B applied to 10 other wafers has 9, 9, 8, 14, 8, 13, 11, 5, 7, 6 imperfections. Treat the counts as independent Poisson variates having means μA and B. Consider the model log μ = a + Bx, where x = 1 for treatment B and x = 0 for treatment A. a. Show that ß = log Blog μA = log(B/A) and eß = μb/MA. the addel. Report the prediction eation and interpret 8. SO et H: A B by conducting the Wald or likelihood-ratio test of Ho: B = 0. Interpret. d. Construct a 95% confidence interval for B/A. [Hint: Construct one for B = log(μB/μA) and then exponentiate.]
An experiment analyzes imperfection rates for two processes used to fabricate silicon wafers for computer chips. For treatment A applied to 10 wafers, the numbers of imperfections are 8, 7, 6, 6, 3, 4, 7, 2, 3, 4. Treatment B applied to 10 other wafers has 9, 9, 8, 14, 8, 13, 11, 5, 7, 6 imperfections. Treat the counts as independent Poisson variates having means μA and B. Consider the model log μ = a + Bx, where x = 1 for treatment B and x = 0 for treatment A. a. Show that ß = log Blog μA = log(B/A) and eß = μb/MA. the addel. Report the prediction eation and interpret 8. SO et H: A B by conducting the Wald or likelihood-ratio test of Ho: B = 0. Interpret. d. Construct a 95% confidence interval for B/A. [Hint: Construct one for B = log(μB/μA) and then exponentiate.]
MATLAB: An Introduction with Applications
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Please answer question (d)
(a), (b), (c) has already been solved.
![An experiment analyzes imperfection rates for two processes used to fabricate
silicon wafers for computer chips. For treatment A applied to 10 wafers, the
numbers of imperfections are 8, 7, 6, 6, 3, 4, 7, 2, 3, 4. Treatment B applied to
10 other wafers has 9, 9, 8, 14, 8, 13, 11, 5, 7, 6 imperfections. Treat the counts
as independent Poisson variates having means μA and µg. Consider the model
log μ = a + Bx, where x = 1 for treatment B and x = 0 for treatment A.
a. Show that B =
logμB - log μA = log(μB/A) and eß = μb/MA.
Firthe addel. Report the prediction eation and interpret 8.
Sol
UAB by onducting the Wald or likelihood-ratio test of
Ho: B = 0. Interpret.
d. Construct a 95% confidence interval for B/A. [Hint: Construct one for
B = log(μB/μA) and then exponentiate.]](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F1bda7345-9ae4-4e40-846f-b2b596594f72%2F4db93cd9-5d81-419c-b72b-ba50009f6def%2Fogmvo3i_processed.jpeg&w=3840&q=75)
Transcribed Image Text:An experiment analyzes imperfection rates for two processes used to fabricate
silicon wafers for computer chips. For treatment A applied to 10 wafers, the
numbers of imperfections are 8, 7, 6, 6, 3, 4, 7, 2, 3, 4. Treatment B applied to
10 other wafers has 9, 9, 8, 14, 8, 13, 11, 5, 7, 6 imperfections. Treat the counts
as independent Poisson variates having means μA and µg. Consider the model
log μ = a + Bx, where x = 1 for treatment B and x = 0 for treatment A.
a. Show that B =
logμB - log μA = log(μB/A) and eß = μb/MA.
Firthe addel. Report the prediction eation and interpret 8.
Sol
UAB by onducting the Wald or likelihood-ratio test of
Ho: B = 0. Interpret.
d. Construct a 95% confidence interval for B/A. [Hint: Construct one for
B = log(μB/μA) and then exponentiate.]
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