Essay – Athlete’s high salaries. Should they be paid that amount or not?

Essay – Athlete’s high salaries. Should they be paid that amount or not?

Athlete’s high salaries: Should they be paid that amount or … Read More...
How many way can Chicago get High Scores when know Chicago score is 18 point in football game and the point are score as Safety 2 points Filed goal 3 points Touchdown 6 points & can get extra 2 points or 0 points

How many way can Chicago get High Scores when know Chicago score is 18 point in football game and the point are score as Safety 2 points Filed goal 3 points Touchdown 6 points & can get extra 2 points or 0 points

  Strategy: I would to use eliminating possibilities strategy   … Read More...
CIS 343 Homework #1 1. In the game of “craps” two dice are thrown and the outcome of a bet is based on the sum of the two dice. If you bet $1 that the sum is “seven” then you win $4 or lose your dollar. The probability that you win is 6/36=1/6, and P(loss) = 5/6. Find a rough range for a) 200 plays, (b) 20, 000 plays. You must show your work when you compute the SD of the box! [Hint: There are four steps in solving this problem. 1. You must first find the box model, the simplest model has six tickets in the box with some of the tickets +4 and others –1. You must determine how many of each of those two numbers are in the box. 2. Next find the Average of the box and the SD of the box, use “n” not “(n-1)” to compute the SD. 3. Third compute Expected(Winnings)=m•AveOfBox and SD(Winnings)=√m•SDofBox, where m is the number of plays. 4. Finally the Rough Range is Expected(Win)±SD(Win).] 2. Work out the average and SD for the following list: a) 1, 3, 4, 5, 7 Then work out the average and SD for the next list: b) 6, 8, 9, 10, 12 Use n-1 in computing the SD. Are you surprised by the answers? 3. Use “n” in computing SD’s for this problem. a) A list has 10 numbers, each number is a 1, or 2, or 3. If the average is 2 and the SD is 0, find the list. b) A second list has 10 numbers, each number is a 1, or 2, or 3. If the SD is 1, find the list. c) Can the SD be bigger than 1? [This problem is solved by trial and error. Think what center and spread mean! You do not need to use every number for every list. If you do not like the number 3, you may not have to use it] 4. Find the population standard deviation for the following four populations: a) 1, 2, 3, 4, 5 b) 1, 2, 3, 4, 5, 1, 2, 3, 4, 5 [Divide by 5 for the population in a), divide by 10 for the population in b).] c) 2, -1, -1, -1 d) 2, -1, -1, -1, 2, -1, -1, -1 [Divide by 4 for the population in c), divide by 8 for the population in d).]

CIS 343 Homework #1 1. In the game of “craps” two dice are thrown and the outcome of a bet is based on the sum of the two dice. If you bet $1 that the sum is “seven” then you win $4 or lose your dollar. The probability that you win is 6/36=1/6, and P(loss) = 5/6. Find a rough range for a) 200 plays, (b) 20, 000 plays. You must show your work when you compute the SD of the box! [Hint: There are four steps in solving this problem. 1. You must first find the box model, the simplest model has six tickets in the box with some of the tickets +4 and others –1. You must determine how many of each of those two numbers are in the box. 2. Next find the Average of the box and the SD of the box, use “n” not “(n-1)” to compute the SD. 3. Third compute Expected(Winnings)=m•AveOfBox and SD(Winnings)=√m•SDofBox, where m is the number of plays. 4. Finally the Rough Range is Expected(Win)±SD(Win).] 2. Work out the average and SD for the following list: a) 1, 3, 4, 5, 7 Then work out the average and SD for the next list: b) 6, 8, 9, 10, 12 Use n-1 in computing the SD. Are you surprised by the answers? 3. Use “n” in computing SD’s for this problem. a) A list has 10 numbers, each number is a 1, or 2, or 3. If the average is 2 and the SD is 0, find the list. b) A second list has 10 numbers, each number is a 1, or 2, or 3. If the SD is 1, find the list. c) Can the SD be bigger than 1? [This problem is solved by trial and error. Think what center and spread mean! You do not need to use every number for every list. If you do not like the number 3, you may not have to use it] 4. Find the population standard deviation for the following four populations: a) 1, 2, 3, 4, 5 b) 1, 2, 3, 4, 5, 1, 2, 3, 4, 5 [Divide by 5 for the population in a), divide by 10 for the population in b).] c) 2, -1, -1, -1 d) 2, -1, -1, -1, 2, -1, -1, -1 [Divide by 4 for the population in c), divide by 8 for the population in d).]

info@checkyourstudy.com Operations Team Whatsapp( +91 9911743277) CIS 343 Homework #1  1.  … Read More...
Project Part 1 Objective Our objective, in this Part 1 of our Project, is to practise solving a problem by composing and testing a Python program using all that we have learnt so far and discovering new things, such as lists of lists, on the way. Project – Hunting worms in our garden! No more turtles! In this project, we shall move on to worms. Indeed, our project is a game in which the player hunts for worms in our garden. Once our garden has been displayed, the player tries to guess where the worms are located by entering the coordinates of a cell in our garden. When the player has located all the worms, the game is over! Of course there are ways of making this game more exciting (hence complicated), but considering that we have 2 weeks for Part 1 and 2 weeks for Part 2, keeping it simple will be our goal. We will implement our game in two parts. In Part 1, we write code that constructs and tests our data structures i.e., our variables. In Part 2, we write code that allows the player to play a complete “worm hunting” game! ? Project – Part 1 – Description Data Structures (variables): As stated above, in Part 1, we write code that constructs our data structures i.e., our variables. In our game program, we will need data structures (variables) to represent: 1. Our garden that is displayed to the player (suggestion: list of lists), 2. The garden that contains all the worms (suggestion: another list of lists), Garden: Our garden in Part 1 of our Project will have a width and a height of 10. Warning: The width and the height of our garden may change in Part 2 of our Project. So, it may be a good idea to create 2 variables and assign the width and the height of our garden to these 2 variables. 3. Our worms and their information. For each worm, we may want to keep the following information: a. worm number, b. the location of the worm, for example, either the coordinates of the cells containing the worm OR the coordinate of the first cell containing the worm, its length and whether the worm is laying horizontally or vertically. Worms: We will create 6 worms of length 3. 4. And other variables as needed. Testing our data structures: ? Suggestion: as we create a data structure (the “displayed” garden, the garden containing the worms, each worm, etc…), print it with a “debug print statement”. Once we are certain the data structure is well constructed, comment out the “debug print statement”. Code: In Part 1, the code we write must include functions and it must include the main section of our program. In other words, in Part 1, the code we write must be a complete program. In terms of functions, here is a list of suggestions. We may have functions that … ? creates a garden (i.e., a garden data structure), ? creates the worms (i.e., the worm data structure), ? places a worm in the garden that is to hold the worms (i.e., another garden data structure), ? displays the garden on the screen for the player to see, ? displays a worm in the displayed garden, ? etc… ? Finally, in Part 1, the code we write must implement the following algorithm: Algorithm: Here is the algorithm for the main section of our game program: ? Welcome the player ? Create an empty “displayed” garden, (“displayed” because this is the garden we display to the player) ? Create the worms (worms’ information) ? Create an empty “hidden” garden Note 1: “hidden” because one can keep track of the worms in this “hidden” garden, which we do not show to the player. This is why it is called “hidden”. Note 2: One can keep track of worm’s locations using a different mechanism or data structure. It does not have to be a list of lists representing a “hidden” garden. We are free to choose how we want to keep track of where our worms are located in our garden. ? Place each worm in the “hidden” garden (or whatever mechanism or data structure we decide to use) ? Display the “displayed” garden on the screen for the player to see ? While the player wants to play, ask the player for a worm number (1 to 6), read this worm number and display this worm on the “displayed” garden. This is not the game. Remember, we shall implement the game itself in Part 2. Here, in this step, we make sure our code works properly, i.e., it can retrieve worm information and display worms properly. Displaying worms properly: Note that when we create worms and display them, it may be the case that worms overlap with other worms and that worms wrap around the garden. These 2 situations are illustrated in the 3 Sample Runs discussed below. At this point, we are ready for Part 2 of our Project. Sample Runs: In order to illustrate the explanations given above of what we are to do in this Part 1 of our Project, 3 sample runs have been posted below the description of this Part 1 of our Project on our course web site. Have a look at these 3 sample runs. The code we create for this Part 1 of our Project must produce exactly the same output as the one shown in these 3 sample runs. Of course, the position of our worms will be different but everything else should be the same. What we see in each of these 3 sample runs is 1 execution of the code we are to create for this Part 1 of our Project. Note about Sample Run 1: In this Sample Run, the player enters the numbers 1 to 8 sequentially. Wrap around: Worm 2 wraps around: it starts at (row 7, column B), (row 7, column A) then wraps around to (row 7, column J). Worm 6 also wraps around: it starts at (row 2, column E), (row 1, column E) then wraps around to (row 10, column E). Overlap: There are some overlapping worms: worms 5 and 6 overlap at (row 1, column E). Note about Sample Run 2: In this Sample Run, the player enters the numbers 1 to 8 sequentially. Wrap around: Worm 3 wraps around: it starts at (row 1, column B) then wraps around to (row 10, column B) and (row 9, column B). Worm 6 also wraps around: it starts at (row 1, column D) then wraps around to (row 10, column D) and (row 9, column D). Overlap: There are some overlapping worms: worms 2 and 4 overlap at (row 3, column H), worms 1 and 2 overlap at (row 3, column G) and worms 2 and 5 overlap at (row 3, column E). Note about Sample Run 3: In this Sample Run, the player enters the numbers in the following sequence: 3, 2, 6, 4, 5, 1, 7, 8. Wrap around: Worm 3 wraps around: it starts at (row 2, column C), (row 1, column C) then wraps around to (row 10, column C). Worm 1 also wraps around: it starts at (row 2, column B), (row 2, column A) then wraps around to (row 2, column J). Overlap: There are some overlapping worms: worms 6 and 3 overlap at (row 1, column C) and (row 2, column C). Other Requirements: Here are a few more requirements the code we are to create for this Part 1 of our Project must satisfy. 1. The location of each worm in the garden must be determined randomly. 2. Whether a worm is lying horizontally or vertically must also be determined randomly. 3. It is acceptable in Part 1 of our Project if worms overlap each other (see Sample Runs) 4. When placing a worm in a garden, the worm must “wrap around” the garden. See Sample Runs for examples of what “wrapping around” signifies. How will we implement this wrapping around? Hint: wrapping around can be achieved using an arithmetic operator we have already seen. 5. We must make use of docstring when we implement our functions (have a look at our textbook for an explanation and an example). 6. Every time we encounter the word must in this description of Part 1 of our Project, we shall look upon that sentence as another requirement. For example, the sentence “The code we create for this Part 1 of our Project must produce exactly the same output as the one shown in these 3 sample runs.”, even though it is not listed below the Other Requirements heading, is also a requirement because of its must.

Project Part 1 Objective Our objective, in this Part 1 of our Project, is to practise solving a problem by composing and testing a Python program using all that we have learnt so far and discovering new things, such as lists of lists, on the way. Project – Hunting worms in our garden! No more turtles! In this project, we shall move on to worms. Indeed, our project is a game in which the player hunts for worms in our garden. Once our garden has been displayed, the player tries to guess where the worms are located by entering the coordinates of a cell in our garden. When the player has located all the worms, the game is over! Of course there are ways of making this game more exciting (hence complicated), but considering that we have 2 weeks for Part 1 and 2 weeks for Part 2, keeping it simple will be our goal. We will implement our game in two parts. In Part 1, we write code that constructs and tests our data structures i.e., our variables. In Part 2, we write code that allows the player to play a complete “worm hunting” game! ? Project – Part 1 – Description Data Structures (variables): As stated above, in Part 1, we write code that constructs our data structures i.e., our variables. In our game program, we will need data structures (variables) to represent: 1. Our garden that is displayed to the player (suggestion: list of lists), 2. The garden that contains all the worms (suggestion: another list of lists), Garden: Our garden in Part 1 of our Project will have a width and a height of 10. Warning: The width and the height of our garden may change in Part 2 of our Project. So, it may be a good idea to create 2 variables and assign the width and the height of our garden to these 2 variables. 3. Our worms and their information. For each worm, we may want to keep the following information: a. worm number, b. the location of the worm, for example, either the coordinates of the cells containing the worm OR the coordinate of the first cell containing the worm, its length and whether the worm is laying horizontally or vertically. Worms: We will create 6 worms of length 3. 4. And other variables as needed. Testing our data structures: ? Suggestion: as we create a data structure (the “displayed” garden, the garden containing the worms, each worm, etc…), print it with a “debug print statement”. Once we are certain the data structure is well constructed, comment out the “debug print statement”. Code: In Part 1, the code we write must include functions and it must include the main section of our program. In other words, in Part 1, the code we write must be a complete program. In terms of functions, here is a list of suggestions. We may have functions that … ? creates a garden (i.e., a garden data structure), ? creates the worms (i.e., the worm data structure), ? places a worm in the garden that is to hold the worms (i.e., another garden data structure), ? displays the garden on the screen for the player to see, ? displays a worm in the displayed garden, ? etc… ? Finally, in Part 1, the code we write must implement the following algorithm: Algorithm: Here is the algorithm for the main section of our game program: ? Welcome the player ? Create an empty “displayed” garden, (“displayed” because this is the garden we display to the player) ? Create the worms (worms’ information) ? Create an empty “hidden” garden Note 1: “hidden” because one can keep track of the worms in this “hidden” garden, which we do not show to the player. This is why it is called “hidden”. Note 2: One can keep track of worm’s locations using a different mechanism or data structure. It does not have to be a list of lists representing a “hidden” garden. We are free to choose how we want to keep track of where our worms are located in our garden. ? Place each worm in the “hidden” garden (or whatever mechanism or data structure we decide to use) ? Display the “displayed” garden on the screen for the player to see ? While the player wants to play, ask the player for a worm number (1 to 6), read this worm number and display this worm on the “displayed” garden. This is not the game. Remember, we shall implement the game itself in Part 2. Here, in this step, we make sure our code works properly, i.e., it can retrieve worm information and display worms properly. Displaying worms properly: Note that when we create worms and display them, it may be the case that worms overlap with other worms and that worms wrap around the garden. These 2 situations are illustrated in the 3 Sample Runs discussed below. At this point, we are ready for Part 2 of our Project. Sample Runs: In order to illustrate the explanations given above of what we are to do in this Part 1 of our Project, 3 sample runs have been posted below the description of this Part 1 of our Project on our course web site. Have a look at these 3 sample runs. The code we create for this Part 1 of our Project must produce exactly the same output as the one shown in these 3 sample runs. Of course, the position of our worms will be different but everything else should be the same. What we see in each of these 3 sample runs is 1 execution of the code we are to create for this Part 1 of our Project. Note about Sample Run 1: In this Sample Run, the player enters the numbers 1 to 8 sequentially. Wrap around: Worm 2 wraps around: it starts at (row 7, column B), (row 7, column A) then wraps around to (row 7, column J). Worm 6 also wraps around: it starts at (row 2, column E), (row 1, column E) then wraps around to (row 10, column E). Overlap: There are some overlapping worms: worms 5 and 6 overlap at (row 1, column E). Note about Sample Run 2: In this Sample Run, the player enters the numbers 1 to 8 sequentially. Wrap around: Worm 3 wraps around: it starts at (row 1, column B) then wraps around to (row 10, column B) and (row 9, column B). Worm 6 also wraps around: it starts at (row 1, column D) then wraps around to (row 10, column D) and (row 9, column D). Overlap: There are some overlapping worms: worms 2 and 4 overlap at (row 3, column H), worms 1 and 2 overlap at (row 3, column G) and worms 2 and 5 overlap at (row 3, column E). Note about Sample Run 3: In this Sample Run, the player enters the numbers in the following sequence: 3, 2, 6, 4, 5, 1, 7, 8. Wrap around: Worm 3 wraps around: it starts at (row 2, column C), (row 1, column C) then wraps around to (row 10, column C). Worm 1 also wraps around: it starts at (row 2, column B), (row 2, column A) then wraps around to (row 2, column J). Overlap: There are some overlapping worms: worms 6 and 3 overlap at (row 1, column C) and (row 2, column C). Other Requirements: Here are a few more requirements the code we are to create for this Part 1 of our Project must satisfy. 1. The location of each worm in the garden must be determined randomly. 2. Whether a worm is lying horizontally or vertically must also be determined randomly. 3. It is acceptable in Part 1 of our Project if worms overlap each other (see Sample Runs) 4. When placing a worm in a garden, the worm must “wrap around” the garden. See Sample Runs for examples of what “wrapping around” signifies. How will we implement this wrapping around? Hint: wrapping around can be achieved using an arithmetic operator we have already seen. 5. We must make use of docstring when we implement our functions (have a look at our textbook for an explanation and an example). 6. Every time we encounter the word must in this description of Part 1 of our Project, we shall look upon that sentence as another requirement. For example, the sentence “The code we create for this Part 1 of our Project must produce exactly the same output as the one shown in these 3 sample runs.”, even though it is not listed below the Other Requirements heading, is also a requirement because of its must.

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Think about a game of tug-of-war with your friends. If both sides are pulling and neither side is moving, then the forces are balanced. How would you describe the forces if one person is taken away from the game?

Think about a game of tug-of-war with your friends. If both sides are pulling and neither side is moving, then the forces are balanced. How would you describe the forces if one person is taken away from the game?

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Engineering Risk Management Special topic: Beer Game Copyright Old Dominion University, 2017 All rights reserved Revised Class Schedule Lac-Megantic Case Study Part 1: Timeline of events Part 2: Timeline + causal chain of events Part 3: Instructions Evaluate your causal-chain (network) Which are the root causes? Which events have the most causes? What are the relationship of the causes? Which causes have the most influence? Part 4: Instructions Consider these recommendations from TSB Which nodes in your causal chain will be addressed by which of these recommendations? Recap How would you summarize the steps in conducting post-event analysis of an accident? Beer Game Case Study The beer game was developed at MIT in the 1960s. It is an experiential learning business simulation game created by a group of professors at MIT Sloan School of Management in early 1960s to demonstrate a number of key principles of supply chain management. The game is played by teams of four players, often in heated competition, and takes at least one hour to complete.  Beer Game Case Study Beer Game Case Study A truck driver delivers beer once each week to the retailer. Then the retailer places an order with the trucker who returns the order to the wholesaler. There’s a four week lag between ordering and receiving the beer. The retailer and wholesaler do not communicate directly. The retailer sells hundreds of products and the wholesaler distributes many products to a large number of customers. Beer Game Case Study The Retailer Week 1: Lover’s Beer is not very popular but the retailer sells four cases per week on average. Because the lead time is four weeks, the retailer attempts to keep twelve cases in the store by ordering four cases each Monday when the trucker makes a delivery. Week 2: The retailer’s sales of Lover’s beer doubles to eight cases, so on Monday, he orders 8 cases. Week 3: The retailer sells 8 cases. The trucker delivers four cases. To be safe, the retailer decides to order 12 cases of Lover’s beer. Week 4: The retailer learns from some of his younger customers that a music video appearing on TV shows a group singing “I’ll take on last sip of Lover’s beer and run into the sun.” The retailer assumes that this explains the increased demand for the product. The trucker delivers 5 cases. The retailer is nearly sold out, so he orders 16 cases. Beer Game Case Study The Retailer Week 5: The retailer sells the last case, but receives 7 cases. All 7 cases are sold by the end of the week. So again on Monday the retailer orders 16 cases. Week 6: Customers are looking for Lover’s beer. Some put their names on a list to be called when the beer comes in. The trucker delivers only 6 cases and all are sold by the weekend. The retailer orders another 16 cases. Week 7: The trucker delivers 7 cases. The retailer is frustrated, but orders another 16 cases. Week 8: The trucker delivers 5 cases and tells the retailer the beer is backlogged. The retailer is really getting irritated with the wholesaler, but orders 24 cases. Beer Game Case Study The Wholesaler The wholesaler distributes many brands of beer to a large number of retailers, but he is the only distributor of Lover’s beer. The wholesaler orders 4 truckloads from the brewery truck driver each week and receives the beer after a 4 week lag. The wholesaler’s policy is to keep 12 truckloads in inventory on a continuous basis. Week 6: By week 6 the wholesaler is out of Lover’s beer and responds by ordering 30 truckloads from the brewery. Week 8: By the 8th week most stores are ordering 3 or 4 times more Lovers’ beer than their regular amounts. Week 9: The wholesaler orders more Lover’s beer, but gets only 6 truckloads. Week 10: Only 8 truckloads are delivered, so the wholesaler orders 40. Week 11: Only 12 truckloads are received, and there are 77 truckloads in backlog, so the wholesaler orders 40 more truckloads. Beer Game Case Study The Wholesaler Week 12: The wholesaler orders 60 more truckloads of Lover’s beer. It appears that the beer is becoming more popular from week to week. Week 13: There is still a huge backlog. Weeks 14-15: The wholesaler receives larger shipments from the brewery, but orders from retailers begin to drop off. Week 16: The trucker delivers 55 truckloads from the brewery, but the wholesaler gets zero orders from retailers. So he stops ordering from the brewery. Week 17: The wholesaler receives another 60 truckloads. Retailers order zero. The wholesaler orders zero. The brewery keeps sending beer. Beer Game Case Study The Brewery The brewery is small but has a reputation for producing high quality beer. Lover’s beer is only one of several products produced at the brewery. Week 6: New orders come in for 40 gross. It takes two weeks to brew the beer. Week 14: Orders continue to come in and the brewery has not been able to catch up on the backlogged orders. The marketing manager begins to wonder how much bonus he will get for increasing sales so dramatically. Week 16: The brewery catches up on the backlog, but orders begin to drop off. Week 18: By week 18 there are no new orders for Lover’s beer. Week 19: The brewery has 100 gross of Lover’s beer in stock, but no orders. So the brewery stops producing Lover’s beer. Weeks 20-23. No orders. Beer Game Case Study At this point all the players blame each other for the excess inventory. Conversations with wholesale and retailer reveal an inventory of 93 cases at the retailer and 220 truckloads at the wholesaler. The marketing manager figures it will take the wholesaler a year to sell the Lover’s beer he has in stock. The retailers must be the problem. The retailer explains that demand increased from 4 cases per week to 8 cases. The wholesaler and marketing manager think demand mushroomed after that, and then fell off, but the retailer explains that didn’t happen. Demand stayed at 8 cases per week. Since he didn’t get the beer he ordered, he kept ordering more in an attempt to keep up with the demand. The marketing manager plans his resignation. Homework 4 Read the case and answer 1+6 questions. 0th What should go right? 1st What can go wrong? 2nd What are the causes and consequences? 3rd What is the likelihood of occurrence? 4rd What can be done to detect, control, and manage them? 5th What are the alternatives? 6th What are the effects beyond this particular time? Homework 4 In 500 words or less, summarize lessons learned in this beer game as it relates to supply chain risk management. Apply one of the tools (CCA, HAZOP, FMEA, etc.) to the case. Work individually and submit before Monday midnight (Feb. 20th). No class on Monday (Feb. 20th).

Engineering Risk Management Special topic: Beer Game Copyright Old Dominion University, 2017 All rights reserved Revised Class Schedule Lac-Megantic Case Study Part 1: Timeline of events Part 2: Timeline + causal chain of events Part 3: Instructions Evaluate your causal-chain (network) Which are the root causes? Which events have the most causes? What are the relationship of the causes? Which causes have the most influence? Part 4: Instructions Consider these recommendations from TSB Which nodes in your causal chain will be addressed by which of these recommendations? Recap How would you summarize the steps in conducting post-event analysis of an accident? Beer Game Case Study The beer game was developed at MIT in the 1960s. It is an experiential learning business simulation game created by a group of professors at MIT Sloan School of Management in early 1960s to demonstrate a number of key principles of supply chain management. The game is played by teams of four players, often in heated competition, and takes at least one hour to complete.  Beer Game Case Study Beer Game Case Study A truck driver delivers beer once each week to the retailer. Then the retailer places an order with the trucker who returns the order to the wholesaler. There’s a four week lag between ordering and receiving the beer. The retailer and wholesaler do not communicate directly. The retailer sells hundreds of products and the wholesaler distributes many products to a large number of customers. Beer Game Case Study The Retailer Week 1: Lover’s Beer is not very popular but the retailer sells four cases per week on average. Because the lead time is four weeks, the retailer attempts to keep twelve cases in the store by ordering four cases each Monday when the trucker makes a delivery. Week 2: The retailer’s sales of Lover’s beer doubles to eight cases, so on Monday, he orders 8 cases. Week 3: The retailer sells 8 cases. The trucker delivers four cases. To be safe, the retailer decides to order 12 cases of Lover’s beer. Week 4: The retailer learns from some of his younger customers that a music video appearing on TV shows a group singing “I’ll take on last sip of Lover’s beer and run into the sun.” The retailer assumes that this explains the increased demand for the product. The trucker delivers 5 cases. The retailer is nearly sold out, so he orders 16 cases. Beer Game Case Study The Retailer Week 5: The retailer sells the last case, but receives 7 cases. All 7 cases are sold by the end of the week. So again on Monday the retailer orders 16 cases. Week 6: Customers are looking for Lover’s beer. Some put their names on a list to be called when the beer comes in. The trucker delivers only 6 cases and all are sold by the weekend. The retailer orders another 16 cases. Week 7: The trucker delivers 7 cases. The retailer is frustrated, but orders another 16 cases. Week 8: The trucker delivers 5 cases and tells the retailer the beer is backlogged. The retailer is really getting irritated with the wholesaler, but orders 24 cases. Beer Game Case Study The Wholesaler The wholesaler distributes many brands of beer to a large number of retailers, but he is the only distributor of Lover’s beer. The wholesaler orders 4 truckloads from the brewery truck driver each week and receives the beer after a 4 week lag. The wholesaler’s policy is to keep 12 truckloads in inventory on a continuous basis. Week 6: By week 6 the wholesaler is out of Lover’s beer and responds by ordering 30 truckloads from the brewery. Week 8: By the 8th week most stores are ordering 3 or 4 times more Lovers’ beer than their regular amounts. Week 9: The wholesaler orders more Lover’s beer, but gets only 6 truckloads. Week 10: Only 8 truckloads are delivered, so the wholesaler orders 40. Week 11: Only 12 truckloads are received, and there are 77 truckloads in backlog, so the wholesaler orders 40 more truckloads. Beer Game Case Study The Wholesaler Week 12: The wholesaler orders 60 more truckloads of Lover’s beer. It appears that the beer is becoming more popular from week to week. Week 13: There is still a huge backlog. Weeks 14-15: The wholesaler receives larger shipments from the brewery, but orders from retailers begin to drop off. Week 16: The trucker delivers 55 truckloads from the brewery, but the wholesaler gets zero orders from retailers. So he stops ordering from the brewery. Week 17: The wholesaler receives another 60 truckloads. Retailers order zero. The wholesaler orders zero. The brewery keeps sending beer. Beer Game Case Study The Brewery The brewery is small but has a reputation for producing high quality beer. Lover’s beer is only one of several products produced at the brewery. Week 6: New orders come in for 40 gross. It takes two weeks to brew the beer. Week 14: Orders continue to come in and the brewery has not been able to catch up on the backlogged orders. The marketing manager begins to wonder how much bonus he will get for increasing sales so dramatically. Week 16: The brewery catches up on the backlog, but orders begin to drop off. Week 18: By week 18 there are no new orders for Lover’s beer. Week 19: The brewery has 100 gross of Lover’s beer in stock, but no orders. So the brewery stops producing Lover’s beer. Weeks 20-23. No orders. Beer Game Case Study At this point all the players blame each other for the excess inventory. Conversations with wholesale and retailer reveal an inventory of 93 cases at the retailer and 220 truckloads at the wholesaler. The marketing manager figures it will take the wholesaler a year to sell the Lover’s beer he has in stock. The retailers must be the problem. The retailer explains that demand increased from 4 cases per week to 8 cases. The wholesaler and marketing manager think demand mushroomed after that, and then fell off, but the retailer explains that didn’t happen. Demand stayed at 8 cases per week. Since he didn’t get the beer he ordered, he kept ordering more in an attempt to keep up with the demand. The marketing manager plans his resignation. Homework 4 Read the case and answer 1+6 questions. 0th What should go right? 1st What can go wrong? 2nd What are the causes and consequences? 3rd What is the likelihood of occurrence? 4rd What can be done to detect, control, and manage them? 5th What are the alternatives? 6th What are the effects beyond this particular time? Homework 4 In 500 words or less, summarize lessons learned in this beer game as it relates to supply chain risk management. Apply one of the tools (CCA, HAZOP, FMEA, etc.) to the case. Work individually and submit before Monday midnight (Feb. 20th). No class on Monday (Feb. 20th).

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at one moment in the football game, player A exert a force to the waist on player B. at the same time ,a teammate of A exerts the same sized force to the south on player B. in what direction is B likely to go because of these forces?

at one moment in the football game, player A exert a force to the waist on player B. at the same time ,a teammate of A exerts the same sized force to the south on player B. in what direction is B likely to go because of these forces?

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“No Bats in the Belfry” by Dechaine and Johnson Page 1 by Jennifer M. Dechaine1,2 and James E. Johnson1 1Department of Biological Sciences 2Department of Science Education Central Washington University, Ellensburg, WA NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE Part I – The Basic Question Introduction Imagine going out for a brisk winter snowshoe and suddenly stumbling upon hundreds of bat carcasses littering the forest floor. Unfortunately, this unsettling sight has become all too common in the United States (Figure 1). White-nose syndrome (WNS), first discovered in 2006, has now spread to 20 states and has led to the deaths of over 5.5 million bats (as of January 2012). WNS is a disease caused by the fungus, Pseudogymnoascus destructans. Bats infected with WNS develop white fuzz on their noses (Figure 2, next page) and often exhibit unnatural behavior, such as flying outside during the winter when they should be hibernating. WNS affects at least six different bat species in the United States and quickly decimates bat populations (colony mortality is commonly greater than 90%). Scientists have predicted that if deaths continue at the current rate, several bat species will become locally extinct within 20 years. Bats provide natural pest control by eating harmful insects, such as crop pests and disease carrying insect species, and losing bat populations would have devastating consequences for the U.S. economy. Researchers have sprung into action to study how bats become infected with and transmit P. destructans, but a key component of this research is determining where the fungus came from in the first place. Some have suggested that it is an invasive species from a different country while others think it is a North American fungal species that has recently become better able to cause disease. In this case study, we examine the origin of P. destructans causing WNS in North America. Some Other Important Observations • WNS was first documented at four cave sites in New York State in 2006. • The fungus can be spread among bats by direct contact or spores can be transferred between caves by humans (on clothing) or other animals. • European strains of the fungus occur in low levels across Europe but have led to few bat deaths there. • Bats with WNS frequently awake during hibernation, causing them to use important fat reserves, leading to death. No Bats in the Belfry: The Origin of White- Nose Syndrome in Little Brown Bats Figure 1. Many bats dead in winter from white-nose syndrome. NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 2 Questions 1. What is the basic question of this study and why is it interesting? 2. What specific testable hypotheses can you develop to explain the observations and answer the basic question of this study? Write at least two alternative hypotheses. 3. What predictions about the effects of European strains of P. destructans on North American bats can you make if your hypotheses are correct? Write at least one prediction for each of your hypotheses. Figure 2. White fuzz on the muzzle of a little brown bat indicating infection by the disease. NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 3 Part II – The Hypothesis As discussed in Part I, researchers had preliminary data suggesting that the pathogen causing WNS is an invasive fungal species (P. destructans) brought to North America from Europe. They had also observed that P. destructans occurs on European bats but rarely causes their death. Preliminary research also suggested that one reason that bats have been dying from WNS is that the disorder arouses them from hibernation, causing the bats to waste fat reserves flying during the winter when food is not readily available. These observations led researchers to speculate that European P. destructans will affect North American bat hibernation at least as severely as does North American P. destructans (Warnecke et al. 2012). Questions 1. Explicitly state the researchers’ null (H0 ) and alternative hypotheses (HA) for this study. 2. Describe an experiment you could use to differentiate between these hypotheses (H0 and HA). NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 4 Part III – Experiments and Observations In 2010, Lisa Warnecke and colleagues (2012) isolated P. destructans fungal spores from Europe and North America. They collected 54 male little brown bats (Myotis lucifugus) from the wild and divided these bats equally into three treatment groups. • Group 1 was inoculated with the North American P. destructans spores (NAGd treatment). • Group 2 was inoculated with the European P. destructans spores (EUGd treatment). • Group 3 was inoculated using the inoculation serum with no spores (Control treatment). All three groups were put into separate dark chambers that simulated the environmental conditions of a cave. All bats began hibernating within the first week of the study. The researchers used infrared cameras to examine the bats’ hibernation over four consecutive intervals of 26 days each. They then used the cameras to determine the total number of times a bat was aroused from hibernation during each interval. Questions 1. Use the graph below to predict what the results will look like if the null hypothesis is supported. The total arousal counts in the control treatment at each interval is graphed for you (open bars). Justifiy your predictions. 2. Use the graph below to predict what the results will look like if the null hypothesis is rejected. The total arousal counts in the control treatment at each interval is graphed for you (open bars). Justify your predictions. Null Supported Total Arousal counts Interval Null Rejected Total Arousal counts Interval NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 5 2 Credits: Title block photo by David A. Riggs (http://www.flickr.com/photos/driggs/6933593833/sizes/l/), cropped, used in accordance with CC BY-SA 2.0 (http://creativecommons.org/licenses/by-sa/2.0/). Figure 1 photo by Kevin Wenner/Pennsylvania Game Commision (http://www. portal.state.pa.us/portal/server.pt/document/901415/white-nose_kills_hundreds_of_bats_in_lackawanna_county_pdf ). Figure 2 photo courtesy of Ryan von Linden/New York Department of Environmental Conservation, http://www.flickr.com/photos/usfwshq/5765048289/sizes/l/in/ set-72157626818845664/, used in accordance with CC BY 2.0 (http://creativecommons.org/licenses/by/2.0/deed.en). Case copyright held by the National Center for Case Study Teaching in Science, University at Buffalo, State University of New York. Originally published February 6, 2014. Please see our usage guidelines, which outline our policy concerning permissible reproduction of this work. Part IV – Results Figure 3 (below) shows the real data from the study. There is no data for interval 4 bats that were exposed to the European P. destructans (gray bar) because all of the bats in that group died. Questions 1. How do your predictions compare with the experimental results? Be specific. 2. Do the results support or reject the null hypothesis? 3. If the European P. destructans is causing WNS in North America, how come European bats aren’t dying from the same disease? References U.S. Fish and Wildlife Service. 2012. White-Nose Syndrome. Available at: http://whitenosesyndrome.org/. Last accessed December 20, 2013. Warnecke, L., et al. 2012. Inoculation of bats with European Geomyces destructans supports the novel pathogen hypothesis for the origin of white-nose syndrome. PNAS Online Early Edition: http://www.pnas.org/cgi/ doi/10.1073/pnas.1200374109. Last accessed December 20, 2013. Figure 3. Changes in hibernation patterns in M. lucifugus following inoculation with North American P. destructans (NAGd), European P. destructans (EUGd), or the control serum. Interval Total Arousal counts

“No Bats in the Belfry” by Dechaine and Johnson Page 1 by Jennifer M. Dechaine1,2 and James E. Johnson1 1Department of Biological Sciences 2Department of Science Education Central Washington University, Ellensburg, WA NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE Part I – The Basic Question Introduction Imagine going out for a brisk winter snowshoe and suddenly stumbling upon hundreds of bat carcasses littering the forest floor. Unfortunately, this unsettling sight has become all too common in the United States (Figure 1). White-nose syndrome (WNS), first discovered in 2006, has now spread to 20 states and has led to the deaths of over 5.5 million bats (as of January 2012). WNS is a disease caused by the fungus, Pseudogymnoascus destructans. Bats infected with WNS develop white fuzz on their noses (Figure 2, next page) and often exhibit unnatural behavior, such as flying outside during the winter when they should be hibernating. WNS affects at least six different bat species in the United States and quickly decimates bat populations (colony mortality is commonly greater than 90%). Scientists have predicted that if deaths continue at the current rate, several bat species will become locally extinct within 20 years. Bats provide natural pest control by eating harmful insects, such as crop pests and disease carrying insect species, and losing bat populations would have devastating consequences for the U.S. economy. Researchers have sprung into action to study how bats become infected with and transmit P. destructans, but a key component of this research is determining where the fungus came from in the first place. Some have suggested that it is an invasive species from a different country while others think it is a North American fungal species that has recently become better able to cause disease. In this case study, we examine the origin of P. destructans causing WNS in North America. Some Other Important Observations • WNS was first documented at four cave sites in New York State in 2006. • The fungus can be spread among bats by direct contact or spores can be transferred between caves by humans (on clothing) or other animals. • European strains of the fungus occur in low levels across Europe but have led to few bat deaths there. • Bats with WNS frequently awake during hibernation, causing them to use important fat reserves, leading to death. No Bats in the Belfry: The Origin of White- Nose Syndrome in Little Brown Bats Figure 1. Many bats dead in winter from white-nose syndrome. NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 2 Questions 1. What is the basic question of this study and why is it interesting? 2. What specific testable hypotheses can you develop to explain the observations and answer the basic question of this study? Write at least two alternative hypotheses. 3. What predictions about the effects of European strains of P. destructans on North American bats can you make if your hypotheses are correct? Write at least one prediction for each of your hypotheses. Figure 2. White fuzz on the muzzle of a little brown bat indicating infection by the disease. NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 3 Part II – The Hypothesis As discussed in Part I, researchers had preliminary data suggesting that the pathogen causing WNS is an invasive fungal species (P. destructans) brought to North America from Europe. They had also observed that P. destructans occurs on European bats but rarely causes their death. Preliminary research also suggested that one reason that bats have been dying from WNS is that the disorder arouses them from hibernation, causing the bats to waste fat reserves flying during the winter when food is not readily available. These observations led researchers to speculate that European P. destructans will affect North American bat hibernation at least as severely as does North American P. destructans (Warnecke et al. 2012). Questions 1. Explicitly state the researchers’ null (H0 ) and alternative hypotheses (HA) for this study. 2. Describe an experiment you could use to differentiate between these hypotheses (H0 and HA). NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 4 Part III – Experiments and Observations In 2010, Lisa Warnecke and colleagues (2012) isolated P. destructans fungal spores from Europe and North America. They collected 54 male little brown bats (Myotis lucifugus) from the wild and divided these bats equally into three treatment groups. • Group 1 was inoculated with the North American P. destructans spores (NAGd treatment). • Group 2 was inoculated with the European P. destructans spores (EUGd treatment). • Group 3 was inoculated using the inoculation serum with no spores (Control treatment). All three groups were put into separate dark chambers that simulated the environmental conditions of a cave. All bats began hibernating within the first week of the study. The researchers used infrared cameras to examine the bats’ hibernation over four consecutive intervals of 26 days each. They then used the cameras to determine the total number of times a bat was aroused from hibernation during each interval. Questions 1. Use the graph below to predict what the results will look like if the null hypothesis is supported. The total arousal counts in the control treatment at each interval is graphed for you (open bars). Justifiy your predictions. 2. Use the graph below to predict what the results will look like if the null hypothesis is rejected. The total arousal counts in the control treatment at each interval is graphed for you (open bars). Justify your predictions. Null Supported Total Arousal counts Interval Null Rejected Total Arousal counts Interval NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 5 2 Credits: Title block photo by David A. Riggs (http://www.flickr.com/photos/driggs/6933593833/sizes/l/), cropped, used in accordance with CC BY-SA 2.0 (http://creativecommons.org/licenses/by-sa/2.0/). Figure 1 photo by Kevin Wenner/Pennsylvania Game Commision (http://www. portal.state.pa.us/portal/server.pt/document/901415/white-nose_kills_hundreds_of_bats_in_lackawanna_county_pdf ). Figure 2 photo courtesy of Ryan von Linden/New York Department of Environmental Conservation, http://www.flickr.com/photos/usfwshq/5765048289/sizes/l/in/ set-72157626818845664/, used in accordance with CC BY 2.0 (http://creativecommons.org/licenses/by/2.0/deed.en). Case copyright held by the National Center for Case Study Teaching in Science, University at Buffalo, State University of New York. Originally published February 6, 2014. Please see our usage guidelines, which outline our policy concerning permissible reproduction of this work. Part IV – Results Figure 3 (below) shows the real data from the study. There is no data for interval 4 bats that were exposed to the European P. destructans (gray bar) because all of the bats in that group died. Questions 1. How do your predictions compare with the experimental results? Be specific. 2. Do the results support or reject the null hypothesis? 3. If the European P. destructans is causing WNS in North America, how come European bats aren’t dying from the same disease? References U.S. Fish and Wildlife Service. 2012. White-Nose Syndrome. Available at: http://whitenosesyndrome.org/. Last accessed December 20, 2013. Warnecke, L., et al. 2012. Inoculation of bats with European Geomyces destructans supports the novel pathogen hypothesis for the origin of white-nose syndrome. PNAS Online Early Edition: http://www.pnas.org/cgi/ doi/10.1073/pnas.1200374109. Last accessed December 20, 2013. Figure 3. Changes in hibernation patterns in M. lucifugus following inoculation with North American P. destructans (NAGd), European P. destructans (EUGd), or the control serum. Interval Total Arousal counts

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