Production and Operations Analysis, Seventh Edition
7th Edition
ISBN: 9781478623069
Author: Steven Nahmias, Tava Lennon Olsen
Publisher: Waveland Press, Inc.
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Chapter 12, Problem 66AP
Summary Introduction
Interpretation:
Probability of acceptance.
Concept Introduction:
Probability Distribution Function is a likelihood of an event to occur for discrete random variables. Graphically, it shows how likely variables will fall under the probability area.
Exponential distribution is a probabilitydistribution which finds probability of an event to occur between independent constant rate and continous rate.
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Consider the following double sampling plan. First select a sample of 5 from a lotof 100. If there are four or more defectives in the sample, reject the lot. If there isone or fewer defective, accept the lot. If there are two or three defectives, samplean additional five items and reject the lot if the combined number of defectives inboth samples is five or more. If the lot has 10 defectives, what is the probabilitythat a lot passes the inspection?
For the double sampling plan described in Problem 39, determine the following:b. The probability that the lot is rejected based on the second sample.
A company employs the following sampling plan: It draws a sample of 10 percentof the lot being inspected. If 1 percent or less of the sample is defective, the lot isaccepted. Otherwise the lot is rejected.b. If a lot contains 1,000 items of which 20 are defective, what is the probabilitythat the lot is accepted?
A company employs the following sampling plan: It draws a sample of 10 percentof the lot being inspected. If 1 percent or less of the sample is defective, the lot isaccepted. Otherwise the lot is rejected. c. If a lot contains 10,000 items of which 200 are defective, what is the probability that the lot is accepted?
Chapter 12 Solutions
Production and Operations Analysis, Seventh Edition
Ch. 12.1 - Prob. 2PCh. 12.1 - Prob. 3PCh. 12.1 - Prob. 4PCh. 12.1 - Prob. 5PCh. 12.1 - Prob. 6PCh. 12.2 - Prob. 7PCh. 12.2 - Prob. 8PCh. 12.2 - Prob. 9PCh. 12.2 - Prob. 10PCh. 12.2 - Prob. 11P
Ch. 12.2 - Prob. 12PCh. 12.2 - Prob. 13PCh. 12.3 - Prob. 14PCh. 12.3 - Prob. 15PCh. 12.3 - Prob. 16PCh. 12.3 - Prob. 17PCh. 12.4 - Prob. 18PCh. 12.4 - Prob. 19PCh. 12.4 - Prob. 20PCh. 12.4 - Prob. 21PCh. 12.5 - Prob. 22PCh. 12.6 - Prob. 23PCh. 12.6 - Prob. 24PCh. 12.6 - Prob. 25PCh. 12.6 - Prob. 26PCh. 12.6 - Prob. 27PCh. 12.6 - Prob. 28PCh. 12.9 - Prob. 29PCh. 12.9 - Prob. 30PCh. 12.9 - Prob. 31PCh. 12.9 - Prob. 32PCh. 12.9 - Prob. 33PCh. 12.10 - Prob. 34PCh. 12.10 - Prob. 35PCh. 12.10 - Prob. 37PCh. 12.10 - Prob. 38PCh. 12.10 - Prob. 39PCh. 12.10 - Prob. 40PCh. 12.11 - Prob. 41PCh. 12.11 - Prob. 42PCh. 12.11 - Prob. 43PCh. 12.11 - Prob. 44PCh. 12.12 - Prob. 46PCh. 12.12 - Prob. 47PCh. 12.12 - Prob. 48PCh. 12 - Prob. 49APCh. 12 - Prob. 50APCh. 12 - Prob. 51APCh. 12 - Prob. 52APCh. 12 - Prob. 53APCh. 12 - Prob. 54APCh. 12 - Prob. 55APCh. 12 - Prob. 57APCh. 12 - Prob. 58APCh. 12 - Prob. 59APCh. 12 - Prob. 60APCh. 12 - Prob. 61APCh. 12 - Prob. 62APCh. 12 - Prob. 63APCh. 12 - Prob. 64APCh. 12 - Prob. 65APCh. 12 - Prob. 66APCh. 12 - Prob. 67APCh. 12 - Prob. 68APCh. 12 - Prob. 69APCh. 12 - Prob. 70AP
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- Sampling error is defined as: an error that occurs when a sample of less than 30 elements is drawn. an error that occurs during collection, recording, and tabulation of data. the difference between the value of a sample statistic and the value of the corresponding population parameter.arrow_forwardConsider the double sampling plan for Spire CDs described in this section. Over aperiod of one year, 3,860 boxes of records are subject to inspection using this plan.If 60 percent of these batches are “good” (that is, in 60 percent of the batches theproportion of defectives is exactly 10 percent) and 40 percent are “bad” (that is, in40 percent of the batches the proportion of defectives is exactly 30 percent), thenwhat is the expected number of batchesa. Accepted?arrow_forwardConsider the double sampling plan for Spire CDs described in this section. Over aperiod of one year, 3,860 boxes of records are subject to inspection using this plan.If 60 percent of these batches are “good” (that is, in 60 percent of the batches theproportion of defectives is exactly 10 percent) and 40 percent are “bad” (that is, in40 percent of the batches the proportion of defectives is exactly 30 percent), thenwhat is the expected number of batchesd. Accepted on the second sample?arrow_forward
- Consider the double sampling plan for Spire CDs described in this section. Over aperiod of one year, 3,860 boxes of records are subject to inspection using this plan.If 60 percent of these batches are “good” (that is, in 60 percent of the batches theproportion of defectives is exactly 10 percent) and 40 percent are “bad” (that is, in40 percent of the batches the proportion of defectives is exactly 30 percent), thenwhat is the expected number of batchesb. Rejected?arrow_forwardConsider the double sampling plan for Spire CDs described in this section. Over aperiod of one year, 3,860 boxes of records are subject to inspection using this plan.If 60 percent of these batches are “good” (that is, in 60 percent of the batches theproportion of defectives is exactly 10 percent) and 40 percent are “bad” (that is, in40 percent of the batches the proportion of defectives is exactly 30 percent), thenwhat is the expected number of batchese. Rejected on the first sample?arrow_forwardA single sampling inspection scheme for large lot of mass-produced flanges states:From each lot take and inspect a random sample of 50. If 3 or more defectives, inspect the whole lot and remove all defectives, if less than 3 are found accept the lot without further inspection.a. Obtain the equation for Pa the probability that a lot containing a fraction p of defectives will be accepted, in terms of p.b. Evaluate Pa for p=0.01, 0.02, 0.03, 0.05, 0.07, 0.10, 0.15, 0.20, 0.30. Plotthe operating characteristics and average outgoing quality curve.c. Estimate: (a) the producer’s Risk at p of 2% (b) the consumer’s Risk for pof 5%.arrow_forward
- Since each process capability index relies on the estimate of process standard deviation, which in turns relies on sampling, therefore which following statement is INCORRECT? a. Confidence interval of each capability index should be found, instead of computing only a point estimate. b. Each process capability index follows some distribution. c. Each process capability index is a random variable. d. The distribution of Cpk is approximately normal. e. none of the abovearrow_forwardWhat is the meaning of x ~ N (50, 20)? 1. Sampling distribution of x is distributed with a mean of 20 and a standard deviation of 50 2. x-bar is normally distributed with a mean of 20 and a standard deviation of 50 3. x is normally distributed with a mean of 50 and a standard deviation of 20 4. Sampling distribution of x is distributed with a mean of 50 and a standard deviation of 20arrow_forwardWhich of the following statements is NOT true about the process capability ratio? a. The process capability ratio is a ratio for determining whether a process meets design specifications. b. The process capability ratio is computed as the difference of the upper and lower specification limits divided by six standard deviations. c. The process capability ratio is a ratio of the specification to the process variation. d. A capable process has a process capability ratio less than one.arrow_forward
- The general meaning of a standard error is best described by which of the following? a. A standard error is another term for the estimated standard deviation of the population. b. If you go out about two standard errors on either side of 0, you can be about 95% confident that the unknown population parameter will be in the resulting interval. c. A standard error is essentially a standard deviation, specifically, the standard deviation of the sampling distribution of the estimate of the population parameter. d. All of these choices are correct characterizations of a typical standard error.arrow_forwardWhat is the meaning of x ̅ ~ N (50, 2)? 1. The Sampling distribution is distributed normally with a mean of 50 and a standard deviation of 2 2. Sampling distribution of x is distributed normally with a mean of 2 and a standard deviation of 50 3. x is normally distributed with a mean of 50 and a standard deviation of 2 4. x-bar is normally distributed with a mean of 2 and a standard deviation of 50arrow_forwardThe Central Limit Theorem guarantees an approximately normal sampling distribution when n is sufficiently large. A- true B- falsearrow_forward
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