...Lab I – Probability Models When finished fill in the table at the end of this document and email it to your teacher Cards: Use the tab for Cards in the excel file and get the total probability for the various hands All of your inputs are on the yellow cells (a) The first task is to figure how many chances you have for each pick that will result in a successful hand INPUT: columns B/C/D/E/F (b) Then if any of the events (one of the five cards) has 100% chance then you need multiply the one path by five to account for the parallel paths to a successful hand INPUT: column H (c) Finally, if there are more than one way to get the result (example four of a kind can be done with 13 different cards) then you need to add that number too INPUT: column J Note: this step will be more complicated when dealing with royal hands, and multiple runs. (d) Your final probability will be the percentage in the last column in the “prob” row (I’ve formattesd it such that these all fall in rows 7,17,27, etc) Dice: Use the tab for Dice in the excel file and get the probabilities for all the outcomes when tossing three dice Note: this problem has been started with the first result for the outcomes of 3 and 4 The probability also has been simplified to two events (rather that 3) by using the results from lab H for the rolls for dice #2 and #3… see below (also on your excel file) Outcome | theoretical % | total | possible outcomes (die 1 / die 2) | 2 |...
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...the terms of risk reduction and hazard control we get the terms of eliminating and reducing the issues. Where control of hazards seek to maintain instead of removing the process. The term that risk reduction is applied to is a complete understanding of the intent of the criterion to ty risk- reducing the probability of the events occurring. In the terms of the second and third definitions of risk because they include both the probability of the event and the severity of the harmful consequences. Risk reduction is a term that capture the fundamental concept that harmful events consist of the three phases. Jensen, R. C. (2012). Risk-Reduction Methods: For Occupational Safety and Health (1st e A physical model is one that thing would be (like if you were creating a model of say a building, park, airplane or other large structure or area), sometimes it's actual size if it is small enough. You build or have built that you can touch. Sometimes it is a miniature version of what the real. What I mean by physical models is those that are meant to represent the physical world, as opposed to – for example – biomechanical, or computers models. Jensen, R. C. (2012). Risk-Reduction Methods: For Occupational Safety and Health (1st ed.). Whenever you are planning or one have to deal with risk and hazards we should looking in to the process from the beginning to the end. Where do we want to be at this point in the project as we go through...
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...Abstract Model Paper Analyze the different types of abstract models and examples of the problems that are applicable to each type of model. Write the paper in 2–3 pages including the following details: * A brief description of each type of model: * Deterministic * Probability * Simulation * Discipline specific * A brief description of problem for which each model is applicable. * Why each example is applicable to the model for which it was chosen? Present the paper in Microsoft Office Word document format. Name the file A deterministic model is the one that contains no random elements. The output of the model determined the parameter values and the initial conditions. Deterministic models samples include accounting, timetables, pricing, a linear programming model and economic quantity models (Nic, 2013). For example, decision-making problems can be deterministic or probabilistic decision models. As deterministic models, decisions to bring good final outcomes. A deterministic model is “you get what you expect” risk-free model, which determines the outcome. It also depends on the influence of the uncontrollable the factors that determine the outcome of a decision and the information the decision-maker input as a predicting factor (Arsham, 1996). According to Schrodt (2004), deterministic models was widely used in the early 18th century to study physical processes to develop differential equations by many mathematicians. These...
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...CURRICULUM VITAE John Robinson Present Position: Professor, School of Mathematics and Statistics, University of Sydney. Degrees: University of Queensland, B.Sc. (1961) University of Queensland, B.Sc. (Hons II, 1, Mathematics)(1963). University of Sydney, Ph.D. (Mathematical Statistics)(1969). Thesis title: ”Mixtures of Distributions”. Honours: 1984: Elected Member of the International Statistical Institute. 1990: Elected Fellow of the Institute of Mathematical Statistics. 2008: Awarded the Pitman Medal of the Statistical Society of Australia. Positions held: Biometrician, Queensland Department of Primary Industry, 1961-1964. Lecturer, Biometry Section, Department of Agriculture, University of Sydney, 1964-1966. Lecturer, Department of Mathematical Statistics, University of Sydney, 19661971. Senior Lecturer, Department of Mathematical Statistics, University of Sydney, 1972-1982. Associate Professor, Department of Mathematical Statistics, University of Sydney, 1983-1991. Professor, School of Mathematics and Statistics, University of Sydney, 1991Visiting Associate Professor, Department of Statistics, University of Connecticut, 1969-1970. Visiting Associate Professor, Department of Statistics, University of Waterloo, Canada, 1975-1976. Visiting Lecturer, Department of Statistics, University of California, Berkeley, 1979-1980. Visiting Associate Professor, Department of Statistics, University of Rochester, NY, 1986, January-July. Administration: Head of Department of Mathematical Statistics...
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...than three consecutive words from another writer. I also certify that this paper was prepared by me specifically for this course. Student’s Signature: Khanya Clark-Robinson Khanya Clark-Robinson Final Paper Kahneman1, Daniel and Tversky, Amos. (1979). “Prospect Theory: An Analysis of Decision under Risk.” 1. Big Question The big question of this article is how people make decisions under uncertainty of risks and rewards. Decisions under risks assume that a decision can be quantified as a positive or negative outcome with quantifiable probability. This theory was developed for monetary decisions and the process observations can be included in other fields; fields such as social sciences and policy making. 2. Background Information The standard for analyzing decisions was the theory that quantified the outcome and probability. A reasonable individual will choose the option with the best utility. The probability results should all add up to 100%. The utility theory has a defined logical foundation and it represents a behavior with uncertainty and a variety of decisions. At this time it is the approved method that evaluated decisions in science. Although it is utilized in science it lacks the human psychology that enables real life decisions. 3. Limitations of previous work. The expected utility theory fails in certain types of situations. An example would be insurance companies that utilize the expected utility theory. The profits are generated...
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...----------------------- [1] Think about an analogy with another model – a map. There are lots of different types of maps to show different features of the real geography in a s[pic] |hvUhvU5?CJOJQJh LCJOJQJh|CJOJQJhP[OJQJmH sH #h Lh L5?CJOJQJmH sH #h Lh|5?CJOJQJmH sH h~o25?CJOJQJimplified but understandable form. The more ‘realistic’ the map, the less use it will be (you wouldn’t be able to unfold it, for one thing!). [2] Boin A & Lagadec P (2000) Preparing for the Future, Journal of Contingencies and Crisis Management, 8, 4, www.patricklagadec.net/fr/pdf/Preparing_the_future.pdf [3] Some define this probability as the value of this ratio as n tends to infinity [4] Of course, you may be surprised to learn that this is the wrong answer as the coin could land on its edge if left to land on a hard surface. If you Google ‘coin landing on its edge’ you will find that the chance of this happening is thought to be about 1 in 6000 (but we don’t really know!): so the true probabilities of ‘head’ and ‘tail’ are around 0.4999166 and of‘ edge’ around 0.000166667. How much would you pay for a gamble where you win £0 for ‘tails’ and £10 for ‘heads’ but lose your entire family’s wealth if it lands on the edge? Still £3 - £6? [5] Listen to his May 2011 podcast about the feeling of risk http://ihrrblog.org/2011/05/27/prof-paul-slovic-the-feeling-of-risk/ where he talks about the research described in the rest of this lecture. Interesting? [6] “The affect heuristic is a swift, involuntary...
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...Communications of ACM, February 2012: http://dotlrn.aubg.bg/dotlrn/classes/departmentofcomputerscience/sINF370/INF370S12/file-storage/view/Handouts/Privacy_and_Security_-_Emotion_and_Security-Communications_of_ACM-February2012.pdf Make a short resume (about 200 words) of the publication. Responses to presumed threats or attacks are usually emotionally based. People tend to misunderstand or shift their attention to risks that are not very high while forgetting about the not-so-obvious threats. However, these threads are in most cases far more dangerous than the obvious and easy to predict dangers. According to Prospect Theory models individuals tend to weight probability not in the linear fashion advocated by standard normative models of probability theory, but rather the subjective functions that overvalue certain low-probability events. Fear and anger make people anxious and nervous, cause them to make worse decisions and make mistakes. 2. Using AUBG Web find what information security policy, standards, practices and procedures exist. What is the most important for a policy to be effective? http://www.aubg.bg/RapidASPEditor/MyUploadDocs/Information_Security_Guide.pdf For a policy to be effective it needs to be observed and applied. No matter how great a policy is if people do not comply with it it’s useless. 3. Any criticism to the existing at AUBG policies, practices and procedures related to information security, computing and communications as...
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...Quantitative Values Project: Homeowner Master Bathroom Remodel To incorporate quantitative values of expected value and probability into the risk management plan for my master bathroom remodel project will be a challenge. The homeowner is taking on the task of trying to do much of the remodel work himself. Hence the risk is related to human failure. Since the homeowner does not have extensive experience in some of the remodeling tasks, there is no history that can be used to calculate failure rates so that probabilities can be determined. The use of a Human Error Probabilities (HEP) model will be needed to determine the probabilities of the remodel tasks that are most at risk. The tasks that have been identified most at risk are the plumbing, electrical and window installation. I will use the Delphi approach to develop HEP estimates for the most at risk tasks. The first step is to select a panel consisting of four subject matter experts (SME), a risk analysis and a group facilitator. Two of the four SMEs will have professional experience in bathroom remodeling and the other two will be homeowners that have taken on bathroom remodel projects but do not necessarily do it for a living. This is to help minimize biasing the data since the analysis is going to be used to determine whether the homeowner does the work himself or contracts it out. After the facilitator introduces each member of the panel and introductions have been made, the risk analysis will present one of the remodel...
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...Probability and Distributions Abstract This paper will discuss the trends and data values and how they relate to statistical terms. Also will describe the probability of different actions to the same group of data. The data will be broke down accordingly to qualitative and quantitative data, and will be grouped and manipulated to show how the data in each group can prove to be useful in the workplace. Memo To: Head of American Intellectual Union From: Abby Price Date: 3/05/2014 Subject: Data analysis from within the union’s surveys Dear Dr. Common: I will be analyzing data given to me which was taken from a survey within the union from 186 employees. I will discuss probability and how its information is important in the workplace. Overview of the Data Set The data group I was given to analyze has 9 categories: gender, age, department, position, tenure, job satisfaction, intrinsic, extrinsic, and benefits. The employees were asked to rate on a scale of 1-7 on how satisfied they were with the company. Gender, age, department, position and tenure are all qualitative data. This data is acknowledged by a code on the given data but cannot measured unlike the quantitative data: job satisfaction, intrinsic, extrinsic, and benefits. Use of Statistics and Probability in the Real World Statistics are just about everywhere in the business world, from the upper management to the lower line of employees, statistics are very useful and are a huge part of our...
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...PERCENTAGES: THE MOST USEFUL STATISTICS EVER INVENTED Thomas R. Knapp © 2010 "Eighty percent of success is showing up." - Woody Allen “Baseball is ninety percent mental and the other half is physical.” - Yogi Berra "Genius is one percent inspiration and ninety-nine percent perspiration." - Thomas Edison Preface You know what a percentage is. 2 out of 4 is 50%. 3 is 25% of 12. Etc. But do you know enough about percentages? Is a percentage the same thing as a fraction or a proportion? Should we take the difference between two percentages or their ratio? If their ratio, which percentage goes in the numerator and which goes in the denominator? Does it matter? What do we mean by something being statistically significant at the 5% level? What is a 95% confidence interval? Those questions, and much more, are what this book is all about. In his fine article regarding nominal and ordinal bivariate statistics, Buchanan (1974) provided several criteria for a good statistic, and concluded: “The percentage is the most useful statistic ever invented…” (p. 629). I agree, and thus my choice for the title of this book. In the ten chapters that follow, I hope to convince you of the defensibility of that claim. The first chapter is on basic concepts (what a percentage is, how it differs from a fraction and a proportion, what sorts of percentage calculations are useful in statistics...
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...Juan Sanchez Dr. Bridgette McAden MAT 110/50 February 27, 2012 William A. Massey – Mathematician He was born in Jefferson City, Missouri, as the younger of two sons of Richard and Juliette Massey. He is a graduate of the public schools of St. Louis, Missouri and attended high school in University City, a suburb of St. Louis. After receiving a Harvard Book Award and a National Achievement Scholarship at University City High School, he entered Princeton University in 1973. There, he encountered his first real introduction to research mathematics in an honor calculus course taught by the late Ralph Fox. He wrote his undergraduate senior thesis, titled "Galois Connections on Local Fields,'' in algebraic number theory, under the direction of the late Bernard Dwork, and graduated from Princeton in 1977 with an A.B. in Mathematics (Magna Cum Laude, Phi Beta Kappa, and Sigma Xi). That same year he was awarded a Bell Labs Cooperative Research Fellowship for minorities to attend graduate school in the department of mathematics at Stanford University. In 1981, he received his Ph.D. degree from Stanford and his thesis, titled "Non-Stationary Queues,'' was directed by Joseph Keller. Dr. William Massey's parents, Juliette and Richard Massey Sr. were both educators; she was from Chattanooga, Tennessee and he was from Charlotte, North Carolina. They met at Lincoln University in Jefferson City, Missouri which became his birthplace. Professor Massey's initial fascination with numbers...
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...followed and interpreted. Out of this, historical development changes that are important for the company can be recognized and evaluated. Additionally, the relevance and the reliability of the data sources are tested. Furthermore it is checked, where prognoses are required. ③The direction, intensity and speed of environmental trends are explored through environmental forecasting. Especially the search for possible threats is of importance. A prognosis of trends is necessary to get a picture of the future. This is done by adequate methods, like strategic foresight or scenario analysis. Several other methods of forecasting are the following: guessing, rule of thumb, expert judgement, extrapolation, leading indicators, surveys, time-series models and econometric systems. ④ In the last step of the global environmental analysis, the results of the previous three steps...
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...very difficult for me. From manipulating and navigating the ribbons to inserting graphs, pictures, and formulas. According to our textbook, a simulation is the replication “of a real system with a mathematical model that can be analyzed with a computer” (Taylor, p. 805, 2010). The part of setting up a simulation in Excel that I find to be the most challenging is the entire idea of using simulation in Excel. However, there are many resources available that can help me you these challenges. One of the biggest resource available is the World Wide Web. Others helpful resources are my textbook, supplemental instructions within the course shell, tutor, and instructor made available by Strayer University. 2. How do we use pseudorandom numbers in a simulation? How do pseudorandom numbers affect the accuracy of a simulation? Pseudorandom numbers random numbers generated by a mathematical process instead of a physical process. In other words, pseudorandom numbers is a process that appears to be random but is not. The way pseudorandom numbers are use in a simulation is by artificially creating random numbers which are uniformly distributed, the technique should be efficient, and do not reflect any pattern (Taylor, p. 634, 2010). Pseudorandom numbers are also used in, probability and statistics applications large quantities of random numbers are needed. Pseudorandom numbers could affect the subsequent frequencies and greatly alter the accuracy of simulation. 3. What is the role of...
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...through the decisions made in the industry every day by the sponsor or pharmaceutical company sponsoring the investigations product. While the sponsor analysis their data, from a team management point of view, the author must determine the number of sites required to achieve the desired results. It is here were statistics and probability comes into place. In order to determine and try to achieve the desired results within the population allowed, the author must determine the number of sites required in order to achieve the desired results. In Phase II, since the sample size is small, the number of sites is determined based on the number of sites needed. For example, past history shows that in order to enroll 95 subjects, 26 sites must be selected. This is based on achieving the desired results 44% of the time. A decision must be made to determine whether or not the author should contract the same number of sites or determine if a different number of sites will be needed. If the desired results are achieved 44% of the time based on past experiences, then in order to achieve a greater success rate, the author will use probability to...
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...Airlines such as WestJet and JetBlue promote low-cost and high-efficiency carriers by giving extremely competitive fares and outstanding customer service. Reservation system for these airlines are so important that when these companies need to make sweeping IT upgrades, their relationships with customers and their brands can be tarnished if things go awry. This can be seen when in 2009, both airlines upgraded their airline reservation systems, SabreSonic CSS was launch, customers struggled to place reservations, and the WestJet Web Site crashed repeatedly. WestJet’s call centers were also overwhelmed, and customers experienced slowdowns at airports. This delay provoked a deluge of customer dissatisfaction. In addition to the increase in customer complaint calls, customers also took to the Internet to express their displeasure. Angry flyers expressed outrage on Facebook and flooded WestJet’s site, causing the repeated crashes. These problems impact both of the airlines operational activities and decision making to change their initial carrier which had started out as a system designed for smaller start-up airlines to a better carrier. Other than that, both airlines needed more processing power to deal with a far greater volume of customers. They also needed features like the ability to link prices and seat inventories to other airlines with whom they cooperated. Both JetBlue and WestJet contracted with Sabre Holdings to upgrade their airline reservation systems. The differences...
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