Concept explainers
You now have $5000. You will toss a fair coin four times. Before each toss you can bet any amount of your money (including none) on the outcome of the toss. If heads comes up, you win the amount you bet. If tails comes up, you lose the amount you bet. Your goal is to reach $15,000. It turns out that you can maximize your chance of reaching $15,000 by betting either the money you have on hand or $15,000 minus the money you have on hand, whichever is smaller. Use simulation to estimate the probability that you will reach your goal with this betting strategy.
To estimate: The probability that Person X would reach the goal with the betting strategy.
Introduction: Simulation model is the digital prototype of the physical model that helps to forecast the performance of the system or model in the real world.
Explanation of Solution
Formulae to determine the above table:
Output results:
The following table is attained by running the simulation @RISK by placing the cursor at B15:
The gambler reaches the goal about 31.5% of the time
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Chapter 11 Solutions
Practical Management Science
- In this version of dice blackjack, you toss a single die repeatedly and add up the sum of your dice tosses. Your goal is to come as close as possible to a total of 7 without going over. You may stop at any time. If your total is 8 or more, you lose. If your total is 7 or less, the house then tosses the die repeatedly. The house stops as soon as its total is 4 or more. If the house totals 8 or more, you win. Otherwise, the higher total wins. If there is a tie, the house wins. Consider the following strategies: Keep tossing until your total is 3 or more. Keep tossing until your total is 4 or more. Keep tossing until your total is 5 or more. Keep tossing until your total is 6 or more. Keep tossing until your total is 7 or more. For example, suppose you keep tossing until your total is 4 or more. Here are some examples of how the game might go: You toss a 2 and then a 3 and stop for total of 5. The house tosses a 3 and then a 2. You lose because a tie goes to the house. You toss a 3 and then a 6. You lose. You toss a 6 and stop. The house tosses a 3 and then a 2. You win. You toss a 3 and then a 4 for total of 7. The house tosses a 3 and then a 5. You win. Note that only 4 tosses need to be generated for the house, but more tosses might need to be generated for you, depending on your strategy. Develop a simulation and run it for at least 1000 iterations for each of the strategies listed previously. For each strategy, what are the two values so that you are 95% sure that your probability of winning is between these two values? Which of the five strategies appears to be best?arrow_forwardYou have 5 and your opponent has 10. You flip a fair coin and if heads comes up, your opponent pays you 1. If tails comes up, you pay your opponent 1. The game is finished when one player has all the money or after 100 tosses, whichever comes first. Use simulation to estimate the probability that you end up with all the money and the probability that neither of you goes broke in 100 tosses.arrow_forwardA martingale betting strategy works as follows. You begin with a certain amount of money and repeatedly play a game in which you have a 40% chance of winning any bet. In the first game, you bet 1. From then on, every time you win a bet, you bet 1 the next time. Each time you lose, you double your previous bet. Currently you have 63. Assuming you have unlimited credit, so that you can bet more money than you have, use simulation to estimate the profit or loss you will have after playing the game 50 times.arrow_forward
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- Consider the following card game. The player and dealer each receive a card from a 52-card deck. At the end of the game the player with the highest card wins; a tie goes to the dealer. (You can assume that Aces count 1, Jacks 11, Queens 12, and Kings 13.) After the player receives his card, he keeps the card if it is 7 or higher. If the player does not keep the card, the player and dealer swap cards. Then the dealer keeps his current card (which might be the players original card) if it is 9 or higher. If the dealer does not keep his card, he draws another card. Use simulation with at least 1000 iterations to estimate the probability that the player wins. (Hint: See the file Sampling Without Replacement.xlsx, one of the example files, to see a clever way of simulating cards from a deck so that the Same card is never dealt more than once.)arrow_forwardYou are attempting to establish the utility that your boss assigns to a payoff of $1,200. You have established that the utility for a payoff of $0 is zero and the utility for a payoff of $10,000 is one. Your boss has just told you that they would be indifferent between a payoff of $1,200 and a lottery which has a payoff of $10,000 where the probability of losing is 0.9. What is your boss' utility for $1,200? (Round your answer to 1 decimal place.) Utility of $1,200arrow_forwardA NY Times best-selling author wants to write a new book as either volume II of her earlier successful book or an autobiography. She believes that by writing the volume II, given her previous success, she will have a 50% chance of placing it with a major publisher where it should ultimately sell about 40,000 copies. However, the worst-case scenario, if she can’t get a major publisher to take it, then she thinks there is 80% chance of placing it with a smaller publisher, with sales of 30,000 copies. On the other hand, if she writes an autobiography, considering the potential interest in her journey as successful writer, she thinks there will be 40% chance of placing it with a major publisher, and it should result in ultimate sales of about 50,000 copies. If she can’t get a major publisher to take it, the worst-case scenario, she thinks there is a 50% chance of placing it with a smaller publisher, with ultimate sales of 35,000 copies. Construct a decision tree to help this author…arrow_forward
- If a student attends every business analytics class, the probability of passing the course is 0.90; but if the student only attends randomly, then the probability of passing the course is 0.30. If a student fails, he or she can take a makeup exam where the probability of passing is 0.60 if the student has attended every class. This probability of passing the makeup exam drops to 0.20 if the student has attended at random. Passing the course is worth 5 credits. Full-time attendance "costs" 3 credits in terms of energy and time, whereas random attendance "costs" only 1 credit. Draw a decision tree and use the decision tree to decide which is the best attendance pattern to adopt. Assume that all failing students take the makeup exam and that the payoff for failing is equal to 0 credit. Draw a decision tree and determine the payoff for each decision and event node. Which alternative should the student choose?arrow_forwardplease answer all parts of the question within 30 minutes with detailed explanation. Make sure calculation form part of the answer and are in details for better understanding. If calculations are not shown or are poorly done i will surely give negative ratings.arrow_forwardA company looking for venture capitalist funding is deciding on the design of its operating system (OS) for its new phone. The first option is to simply buy the OS from another company. This would result in sales of either 10,000 units if the market is not crowded with similar phones or sales of only 3,000 units if the market is crowded. If the company decides to design its own OS the phone would have sales of 70,000 units if the OS was popular but sales of only 2,000 if the OS was a failure. Suppose that to recoup the cost of designing their own OS the company would need to sell twice as many phones as when they simply buy the OS for the profit from the scenarios to be equal. Which option should the company choose if the probability that the market is/ is not crowded is 50% and the probability that the OS is popular is 75%?arrow_forward
- Practical Management ScienceOperations ManagementISBN:9781337406659Author:WINSTON, Wayne L.Publisher:Cengage,