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Problem 6 Five applicants for a job are ranked according to ability, with being the best. These rankings are unknown to an employer, who simply hires two applicants at random. What is the probability that this employer hires exactly one of the two best applicants? Problem 7 Five motors ( through 5) are available for use, and motor 2 is defective. Motors 1 and 2 come from supplier I, and motors 3, 4, and 5 come from supplierIL. Suppose two motors are randomly selected for use on a particular day (each motor equally likely to be chosen). Let A denote the event that the defective motor is selected and B the event that at least one motor comes from supplierI. Find P(A) and P(B). Use a tree diagram to examine the possible combinations. Problem 8 A large box of fuses contains 10% defectives. Four fuses are randomly selected from the box. Find: a) Probability that exactly one fuse is defective b) Probability that at least one fuse of the four selected is defective Now suppose these four sampled fuses are shipped to a customer before being tested. Assume the cost of fixing a shipment with defective fuses is given by C- 3Y2 where Y is the number of defectives in the shipment of four. Find the expected repair cost E(C)-E(3Y)
Problem 11 Your turn. Write a Matlab program to numerically solve Problem 6. Simulate the random selection of two applicants (out of five) and evaluate whether exactly one of the top two are hired. Do this 1,000 times (use a loop) and use the 1,000 outcomes to calculate the probability asked for in Problem 6. Compare the result to the analytical answer you got in Problem 6. Probability Investigate the Matlab built-in function randperm before you create your algorithm. For example, » x = randperm(5) gives you a vector x that contains the integers 1, 2, 3, 4, 5 (exactly one of each, no repeats) in a random order. So you can just pick off the first two out of five and call those your random selections out of 5 applicants. See me if you have issues getting started The result of your 1,000 outcomes provides a single estimate of the probability. If you run the 1,000 outcomes again, you get a second estimate of the probability, and they wont match. You can estimate the confidence interval by running the 1,000 outcomes many times, sorting the resultant probabilities, and setting bounds. For this problem, generate 1,000 samples of the probability (run the 1,000 outcome experiment 1,000 times).So te 1000 probability estimates (sort), and throw away the lowest 25 and highest 25 probability values (the lowest 2.5% and highest 2.5%). The remaining lowest and highest probability values are your 95% confidence interval. Provide this confidence interval: 95% confidence interval- Finally, repeat the above paragraph. This time set your program to run 5,000 outcomes to get a single estimate of probability. Do this 1,000 times and calculate the 95% confidence interval Did the confidence interval change? Why?
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