Wires manufactured for use in a computer system are specified to have resistances between 0.17 and 0.19 ohms. The actual measured resistances of the wires produced by company A have a normal probability distribution with mean 0.18 ohm and standard deviation 0.007 ohm. (Roundyour answers to four decimal places.)(a) What is the probability that a randomly selected wire from company A's production will meetespecifications?(b) If four of these wires are used in each computer system and all are selected from company A, what is the probability that all four in a randomly selected system will meet the specifications?

Let X be the random variable from normal distribution with mean (μ) = 0.18 and standard deviation…

Answered: Wires manufactured for use in a…

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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The owner of a fish market has an assistant who has determined that the weights of catfish are normally distributed, with a mean of 3.2 pounds and a standard deviation of 0.8 pound. If a sample of 64 fish yields a mean of 3.5 pounds, what is probability of obtaining a sample mean this large or larger? Question 2 options: 0.0001 0.0013 0.0228 0.4987
Example 8.5: Traveling between two campuses of a university in a city via shuttle bus takes, on average, 28 minutes with a standard deviation of 5 minutes. In a given week, a bus transported passengers 40 times. What is the probability that the average transport time was more than 30 minutes? Assume the mean time is measured to the nearest minute
Manufacture of a certain component requires three different machining operations. Machining time for each operation has a normal distribution, and the three times are independent of one another. The mean values are 15, 20, and 30 min, respectively, and the standard deviations are 1, 2, and 1.4 min, respectively. What is the probability that it takes at most 1 hour of machining time to produce a randomly selected component? (Round your answer to four decimal places.)You may need to use the appropriate table in the Appendix of Tables to answer this question.
3. An airline has a baggage weight limit of 50 lb. Suppose that the weight of the baggage checked by an individual passenger is a random variable x with a mean value of 49 lb. If 110 passengers will board a flight, what is the approximate probability that the mean weight for this sample of passengers will exceed the limit if the standard deviation of the baggage weight for this group is 23 lb. ? (Round your answer to three decimal places.)
Suppose x is a normally distributed random variable with mean u =0 and standard deviation o = 1. Find the probability that x < 0.64. O 73.89% 76.11% 23.89% O 26.11%
Answer a and b
Cody took his first physics exam and scored an 80. The population mean for this exam is 70, and the standard deviation is 5. What is the probability of selecting a person with a score greater than Cody’s?
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Two six-sided dice are rolled and the random variable x is the sum of the values produced by each die. a. List the possible outcomes for the variable x, determine the probability for each outcome, and calculate the expected value of x. b. Calculate the variance of x. c. Calculate the standard deviation of x. a. List the possible outcomes for the variable x. Choose the correct answer below. O A. 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 О В. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 ОС. 1,2, 3, 4, 5, 6 O D. 3, 4, 5, 6, 7, 8, 9, 10, 11 Determine the probability for each outcome. Select the correct choice below and fill in the answer boxes to complete your choice. (Type integers or fractions.) O A. P(1) =. P(2) = P(3) = P(4) = P(5) = P(6) = О В. Р/2)- P(3) = , P(4) = , P(5) = P(6) = P(7) = P(8) = P(9) = , P(10)= P(11) = P(12) = %3D O C. P(3) = P(4) = , P(5) = , P(6) = ,P(7) = P(8) = P(9) = P(10) = P(11) = O D. P(1)= , P(2) = , P(3) = P(4) = , P(5) = P(6) = P(7) = P(8) = P(9) = P(10) = P(11) = P(12)…
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Let X1, X2, X3, be a r. s. from normal distribution with mean 0 and variance 1, let the prior distribution of 0 is normal with mean zeroand variance 1. Let L(6,0) = (ô - 0). Find the Bayes estimator of 0
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