Savedroctoring Enabled: Chapter 12 Computer Simulation: Bas... A1You have prepared a coin flipping simulation. In your simulation, a value of less than 0.5 is designated as "Heads". Your simulationgenerates the following random numbers:0.553, 0.268, 0.916, 0.588, 0.237, 0.881, 0.067, 0.817, 0.877, 0.426. (Do not round intermediate calculations.)How many trials ended in the result "Heads"?HeadsHow many trials ended in the result "Tails"?Tails

Answered: You have prepared a coin flipping…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...

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of the applicants are denied on this basis? 5. a. What is the probability that a normal variable exceeds two-sigma limits? (That is, what is the probability of observing a value of the random variable larger than µ + 20 or less than µ – 20?)
Tires that fail in service result in significantly higher replacement costs than those replaced before failure. For an 18-wheeler (that is, a truck with 18 tires), failure on the road costs $300, whereas all 18 tires can be replace prior to failure at a cost of $75 per tire. The probability of failure is given in the following table. Number of Miles 0-5,000 5,001-10,000 10,001-15,000 15,001-20,000 20,001-25,000 Probability of Failure .05 .15 .20 .40 .20 If tires are replaced at multiples of 5,000 miles only, what is the optimal age replacement policy?
At the beginning of each day, a patient in the hospital is classifed into one of the three conditions: good, fair or critical. At the beginning of the next day, the patient will either still be in the hospital and be in good, fair or critical condition or will be discharged in one of three conditions: improved, unimproved, or dead. The transistion probabilities for this situation are Good Fair Critical Good 0.65 0.20 0.05 Fair 0.50 0.30 0.12 Critical 0.51 0.25 0.20 Improved Unimproved Dead Good 0.06 0.03 0.01 Fair 0.03 0.02 0.03 Critical 0.01 0.01 0.02 For example a patient who begins the day in fair condition has a 12% chance of being in critical condition the next day and a 3%…
Miles Filtration, Inc. provides maintenance services for water filtration systems throughout Southern Florida. Customers contact Johnson with requests for maintenance service on their water filtration systems. To estimate service time and the service cost, Johnson’s managers want to predict the repair time necessary for each maintenance request. Hence, repair time in hours is the dependent variable. Repair time is believed to be related to three factors: the number of months since the last maintenance service, the type of repair problem (mechanical or electrical), and the repairperson who performs the repair (Donna Newton or Bob Jones). Data for a sample of 10 service calls are reported in the following table: Develop the multiple regression equation to predict repair time, given the number of months since the last maintenance service, the repairperson, and the type of repair. What are the interpretations of the estimated regression parameters? What does the coefficient of…
CLV = Profit per year X Number of years as a customer (lifetime) less customer acquisition costs And we can use the churn rate % to tell us how many years our average customer stay by dividing 1/churn rate. In our case that is 1/20% = 5 years = customer lifetime. A supermarket chain ran a social media campaign and they got 2,000 new customers. The TOTAL cost of the campaign was $250,000. These customers visited the supermarket 25 times a year. Each customer spends $100 per visit and the supermarket makes a 4% profit margin on the customer’s spend. The retention rate of the customers is 60%. What is their CLV? Assume that the profit margin is based on the customer’s non-discounted spend, then deduct the discount.
Senior executives at an oil company are trying to decide whether to drill for oil in a particular field. It costs the company $750,000 to drill. The company estimates that if oil is found the estimated value will be $3,650,000. At present, the company believes that there is a 48% chance that the field actually contains oil. Before drilling, the company can hire an expert at a cost of $75,000 to perform tests to make a prediction of whether oil is present. Based on a similar test, the probability that the test will predict oil on the field is 0.55. The probability of actually finding oil when oil was predicted is 0.85. The probability of actually finding oil when no oil was predicted is 0.2. What is the EMV if the company hires the expert?
See how sensitive the results in Example 11.2 are to the following changes. For each part, make the change indicated, run the simulation, and comment on any differences between your outputs and the outputs in the example. a. The cost of a new camera is increased to $500. b. The warranty period is decreased to one year. c. The terms of the warranty are changed. If the cam- era fails within one year, the customer gets a new camera for free. However, if the camera fails between 1 year and 1.5 years, the customer pays a pro rata share of the new camera, increasing linearly from 0 to full price. For example, if it fails at 1.2 years, which is 40% of the way from 1 to 1.5, the customer pays 40% of the full price. d. The customer pays $50 up front for an extended warranty. This extends the warranty to three years. This extended warranty is just like the original, so that if the camera fails within three years, the customer gets a new camera for free.
Large-scale integrated (LSI) circuit chips are made in one department of an electronics firm. These chips are incorporated into analog devices that are then encased in epoxy. The yield is not particularly good for LSI manufacture, so the AQL specified by that department is 0.15 while the LTPD acceptable by the assembly department is 0.40. Assume the company is willing to accept a consumer's risk of 10 percent and a producer's risk of 5 percent. Find the sample size. Use Exhibit 10.16. Note: if the exact value of the computed LTPD ÷ AOQ ratio does not appear in Exhibit 10.16, use the next higher ratio. Note: Round up your answer to the next whole number. How would you tell someone to do the test?
The Cook County Lumber Co. has three sawmills that produce boards of different lengths. The following table is a joint frequency distribution based on a random sample of 1,000 boards selected from the lumber inventory. Board Length Sawmill 8ft 10ft 12ft 14ft A 140 100 80 14 B 250 20 100 50 C 160 50 16 20 Based on these data, if a board is selected that is 12 feet long, the probability that it was made at sawmill A is: 0.20 0.24 0.08 0.41
If a binomial distribution applies with a sample size of n = 20, find the probability of at least 7 successes if the probability of a success is 0.25. 0.2142 0.1814 0.3123 0.2333
A toy manufacturer wants to see how long, on average, a new toy captures children's attention. He tests 17 children selected at random and finds that their mean attention span is 27 minutes with a standard deviation of 5 minutes. If we assume that attention spans are normally distributed, find a 90% confidence interval for the mean attention span of children playing with this new toy. Give the lower limit and upper limit of the 90% confidence interval. Carry your intermediate computations to at least three decimal places. Round your answers to one decimal place. (If necessary, consult a list of formulas.) Lower limit: Upper limit:
A design engineer is considering the number of levels of redundancy to buildinto a particular circuit. The circuit will be part of a sensitive piece of equipmentwith cost estimated at $500 per failure. Each additional level of redundancy costs$100. If each component fails at random at a rate of one failure every five years,what level of redundancy most closely equates the cost of the design with the expected failure cost of the equipment over its 10-year life cycle?

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