A particular manufacturer (the vendee) uses sample data sent by a vendor to investigate whether the mean length of rods produced by the vendor's production process is truly 10 mm or more, as claimed by the vendor and desired by the vendee. The production process has a standard deviation of 0.03 mm, the vendor supplies n = 200 items to the vendee, and the vendee uses α = .05 in testing Ho: μ = 10 mm against H₂: µ< 10 mm. If the true mean is really μ = 9.9975 mm, what is the chance that they will make a Type II error? What is the probability that the vendee's test will fail to reject the null hypothesis when in fact μ = 9.9975 mm? (Round to four decimal places as needed.)

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0.1190 is wrong could you please kindly reattempt this?

A particular manufacturer (the vendee) uses sample data sent by a vendor to investigate whether the mean length of
rods produced by the vendor's production process is truly 10 mm or more, as claimed by the vendor and desired by the
vendee. The production process has a standard deviation of 0.03 mm, the vendor supplies n = 200 items to the vendee,
and the vendee uses α = .05 in testing Hỏ: µ = 10 mm against H₂: µ< 10 mm. If the true mean is really μ = 9.9975 mm,
what is the chance that they will make a Type Il error?
What is the probability that the vendee's test will fail to reject the null hypothesis when in fact μ = 9.9975 mm?
(Round to four decimal places as needed.)
Transcribed Image Text:A particular manufacturer (the vendee) uses sample data sent by a vendor to investigate whether the mean length of rods produced by the vendor's production process is truly 10 mm or more, as claimed by the vendor and desired by the vendee. The production process has a standard deviation of 0.03 mm, the vendor supplies n = 200 items to the vendee, and the vendee uses α = .05 in testing Hỏ: µ = 10 mm against H₂: µ< 10 mm. If the true mean is really μ = 9.9975 mm, what is the chance that they will make a Type Il error? What is the probability that the vendee's test will fail to reject the null hypothesis when in fact μ = 9.9975 mm? (Round to four decimal places as needed.)
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The answer is wrong. Please explain how they got 0.6808.

A particular manufacturer (the vendee) uses sample data sent by a vendor to investigate
whether the mean length of rods produced by the vendor's production process is truly 10 mm
or more, as claimed by the vendor and desired by the vendee. The production process has a
standard deviation of 0.03 mm, the vendor supplies n = 200 items to the vendee, and the
vendee uses α = .05 in testing Ho: μ = 10 mm against H₂: μ< 10 mm. If the true mean is really
μ = 9.9975 mm, what is the chance that they will make a Type II error?
What is the probability that the vendee's test will fail to reject the null hypothesis when in fact
μ = 9.9975 mm?
0.1170 (Round to four decimal places as needed.)
That's incorrect.
Correct answer: 0.6808
Your answer:
0.1170
X
Transcribed Image Text:A particular manufacturer (the vendee) uses sample data sent by a vendor to investigate whether the mean length of rods produced by the vendor's production process is truly 10 mm or more, as claimed by the vendor and desired by the vendee. The production process has a standard deviation of 0.03 mm, the vendor supplies n = 200 items to the vendee, and the vendee uses α = .05 in testing Ho: μ = 10 mm against H₂: μ< 10 mm. If the true mean is really μ = 9.9975 mm, what is the chance that they will make a Type II error? What is the probability that the vendee's test will fail to reject the null hypothesis when in fact μ = 9.9975 mm? 0.1170 (Round to four decimal places as needed.) That's incorrect. Correct answer: 0.6808 Your answer: 0.1170 X
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