A tire manufacturer produces tires that have a mean life of at least 20000 miles when the production process is working properly. The operations manager stops the production process if there is evidence that the mean life of the tires is below 20000 miles. I need help with 4 The testable hypotheses in this situation are Ho : µ = 20000 vs HA : µ < 20000.1. Identify the consequences of making a Type I error.A. The manager stops production when it is not necessary.B. The manager stops production when it is necessary.C. The manager does not stop production when it is necessary.D. The manager does not stop production when it is not necessary.2. Identify the consequences of making a Type Il error.A. The manager does not stop production when it is not necessary.B. The manager does not stop production when it is necessary.C. The manager stops production when it is necessary.D. The manager stops production when it is not necessary.To monitor the production process, the operations manager takes a random sample of 35 tires each week and subjects them to destructive testing.They calculate the mean life of the tires in the sample, and if it is less than 19000, they will stop production and recalibrate the machines. They knowbased on past experience that the standard deviation of the tire life is 4000 miles.3. What is the probability that the manager will make a Type I error using this decision rule? Round your answer to four decimal places. 0.0695674. Using this decision rule, what is the power of the test if the actual mean life of the tires is 19150 miles? That is, what is the probability they will rejectHo when the actual average life of the tires is 19150 miles? Round your answer to four decimal places. -0.8957

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Description: A tire manufacturer produces tires that have a mean life of at least 20000 miles when the production process is working properly. The operations manager stops the production process if there is evidence that the mean life of the tires is below 20000

Given data: Mean = 20000 Sample size = 35 Standard deviation = 4000

Answered: A tire manufacturer produces tires that…

MATLAB: An Introduction with Applications

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ISBN:9781119256830

Author:Amos Gilat

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A tire manufacturer produces tires that have a mean life of at least 20000 miles when the production process is working properly. The operations manager stops the production process if there is evidence that the mean life of the tires is below 20000 miles. I need help with 4

The testable hypotheses in this situation are Ho : µ = 20000 vs HA : µ < 20000.
1. Identify the consequences of making a Type I error.
A. The manager stops production when it is not necessary.
B. The manager stops production when it is necessary.
C. The manager does not stop production when it is necessary.
D. The manager does not stop production when it is not necessary.
2. Identify the consequences of making a Type Il error.
A. The manager does not stop production when it is not necessary.
B. The manager does not stop production when it is necessary.
C. The manager stops production when it is necessary.
D. The manager stops production when it is not necessary.
To monitor the production process, the operations manager takes a random sample of 35 tires each week and subjects them to destructive testing.
They calculate the mean life of the tires in the sample, and if it is less than 19000, they will stop production and recalibrate the machines. They know
based on past experience that the standard deviation of the tire life is 4000 miles.
3. What is the probability that the manager will make a Type I error using this decision rule? Round your answer to four decimal places. 0.069567
4. Using this decision rule, what is the power of the test if the actual mean life of the tires is 19150 miles? That is, what is the probability they will reject
Ho when the actual average life of the tires is 19150 miles? Round your answer to four decimal places. -0.8957

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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