...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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...three different approaches to probability theory in decision making and give an example for each theory (6 marks) The 3 different approaches to probability theory are intuition-based probability or A Priori, relative frequency-based probability or empirical probability and subjective probability. In intuition based probability, depends on past experience or opinion of person. An example is if arrival of cake ingredients would be delayed by 3 hours then the baker would predict that the completion of the baking of the particular cake would be delayed by 30% because this statement was based on past experience dealing with similar delay in receiving the ingredients. Equally likely assumed that each outcome of the experiment is equal so equal probability is assigned to each outcome. If there are only 2 outcome then the probability of the outcome would be 50%. An example can be seen in tossing a coin where there are only 2 outcome that is either you will get the head or the tail. Therefore the outcome of getting a tail is equal to getting a head and both equal to 50%. Another example is when we roll a dice. We have 6 possible outcomes and each are equally likely. And the outcome would be 1/6. Relative Frequency Approach or Empirical Probability is ration of the number of outcomes in which a specified event occurs to the number of trial in an actual experiment. It estimates probabilities from experience and observation...
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...situation involving such a possibility.” Risk may vary in different field of study! But definitely the core concept is “Uncertainty”. By nature people have a strong desire against uncertain events! These events can rather be stated as ‘threat’ imperiling their way of life. Consequently the concept of insurance came up with an aim to exclude or minimize those risks! Many proclaimed authors made a careful distinction between objective and subjective risk whilst defining risk. Objective risk is a relative variation of actual loss from expected loss. This variation usually decreases as the number of exposure increases. This type of risk can be measured by using deviation. It is extremely utile to an insurer. On the other hand Subjective risk is the mental uncertainty. This risk varies from individually. In this case, the situation and the perception of an individual determine the level of subjective risk for that very person. Concepts: Distinction from Risk Chance of loss might be a close concept of risk. But it is rather the probability of an event to happen. The chance of loss may be identical for two groups. But risk especially objective risk can be quite different! Chance of loss is defined from two angles like...
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...Probability: Introduction to Basic Concept Uncertainty pervades all aspects of human endeavor. Probability is one of our most important conceptual tools because we use it to assess degrees of uncertainty and thereby to reduce risk. Whether or not one has had formal instruction in this topic, s/he is already familiar with the concept of probability since it pervades almost all aspects of our lives. With out consciously realizing it many of our decisions are based on probability. For example, when you study for an examination, you concentrate more on areas that you feel are likely to be covered on the test. You may cancel or postpone an out door activity if you believe the likelihood of rain is high. In business, probability plays a key role in decision-making. The owner of a retail shoe store, for example, orders heavily in those sizes that s/he believes likely to sell fast. The owner of a movie theatre schedules matinees only during holiday seasons because the chances of filling the theatre are greater at that time. The two companies decide to merge when they believe the probability of success is greater for the consolidated company than for either independently. Some important Definitions: Experiment: Experiment is an act that can be repeated under given conditions. Usually, the exact result of the experiment cannot be predicted with certainly. Unit experiment is known as trial. This means that trial is a special case of experiment. Experiment may be a trial...
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...situation involving such a possibility.” Risk may vary in different field of study! But definitely the core concept is “Uncertainty”. By nature people have a strong desire against uncertain events! These events can rather be stated as ‘threat’ imperiling their way of life. Consequently the concept of insurance came up with an aim to exclude or minimize those risks! Many proclaimed authors made a careful distinction between objective and subjective risk whilst defining risk. Objective risk is a relative variation of actual loss from expected loss. This variation usually decreases as the number of exposure increases. This type of risk can be measured by using deviation. It is extremely utile to an insurer. On the other hand Subjective risk is the mental uncertainty. This risk varies from individually. In this case, the situation and the perception of an individual determine the level of subjective risk for that very person. Concepts: Distinction from Risk Chance of loss might be a close concept of risk. But it is rather the probability of an event to happen. The chance of loss may be identical for two groups. But risk especially objective risk can be quite different! Chance of loss is defined from two angles like...
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... 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 a whole? It...
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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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...be reduced by $500.00 for any cases of accident in the claim. The decision of uncertainly in the present case requires selection between personal and car rental service provided insurance through application of probability concept. Research “Car Accident Statistics, Stats, Auto, Fatal, and Drunk Driving” provides the figure for probabilistic estimation of accidents as the chances of one in 16 cars being the case of collision. Once I got the data for odds of accidents, I focused on accurately interpreting my data to make right decision. I have to find the prediction of advantages of choosing car rental insurance over covering the claim in personal policy in forthcoming section. Interpretation of Data Applying Bayes’ Theorem I chose to use Bayes' theorem as the probability model to interpret my data because it is most applicable to my 2100 mile rental insurance decision. The Bayes' theorem emulates the process of logical inference by determining the degree of confidence in possible conclusions based on the available evidence (Lind, Marchal & Wathen, 2008). Furthermore, this evidence is best stated in terms of subjective probability, where the probability is based on evaluating opinions and information, then estimating this data and finally assigning probability to the outcomes. Therefore, Bayes' theorem is best used for the purpose of predicting...
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...Probability Ravindra S. Gokhale IIM Indore 1 “It is a truth very certain that, when it is not in our power to determine what is true, we ought to follow what is most probable” - Rene Descartes 2 Probability Models Concerned with the study of random (or chance) phenomena Random experiment: An experiment that can result in different outcomes, even though it is repeated in the same manner every time Managerial Implication: Due to this random nature additional capacities for any setup are required Although random, certain statistical regularities are to be captured to form the model Model: An abstraction of real world problem 3 Sample Space A set of all possible outcomes of a random experiment Denoted by ‘S’ Examples: • • • • • • • Tossing of a coin: S = {‘Head’, ‘Tail’} Throwing of a dice: S = {1, 2, 3, 4, 5, 6} Marks of a student in a 20 mark paper with only integer negative marking possible: S = {-20, -19, …, -1, 0, 1, …, 19, 20} Number of people arriving at a bank in a day: S = {0, 1, 2, …} Inspection of parts till one defective part is found: S = {d, gd, ggd, gggd, …} Temperature of a place with a knowledge that it ranges between 10 degrees and 50 degrees: S = {any value between 10 to 50} Speed of a train at a given time, with no other additional information: S = {any value between 0 to infinity} 4 Sample Space (cont…) Discrete sample space: One that contains either finite or countable infinite set of outcomes ...
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...given the strength of firm’s project management capability along with market evaluation of CRM implementation. Market analysis shows that 47% of the company finds that inadaptability of the end-user with CRM applications put the project in jeopardy(Coltman and Devinney, 2007). Data is analyzed for implementation of CRM through different vendors for companies of all range from less than $750K to over $10M. It consists of implementation statistics over the past 10 years. To analyze research data, Bayes’ theorem is selected as the probability model that was close to implementation of CRM project. Statistics and Probability Tutorial(n.d.) states that Bayes’ theorem looks appropriate in the context as it provides logical inference to calculate the degree of confidence based on already gathered evidence. Statistical result of data reflects that the probability of project being failed by a project management methodology is 47%. Conditional probability calculation shows that if there is established project management methodology in the firm there was a 16% chance the project would fail. The CRM research analyst additionally stated that even though a project management is not adequate, failure is not always imminent. Failure also...
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...without addressing the needs or concerns of the patients. With the change in the economy and the reasons for the emergency room being utilized, it is important to take a moment to see how the flow of the delivery of services can be confined to smooth transitions. This paper will include appropriate probability concepts, rationale, statistical analysis, and a decision tailored to research studies specific to the thesis statement, question response types, and classification of our findings. Thesis Question "Does the emergency room get utilized more by a particular race and is there a reason for this occurrence?" Appropriate Probability Concepts and Your Application of Them to Find Resulting Data To Limit the Uncertainty of this Decision Probability theory is an important part of statistical theory that bridges descriptive and inferential statistics. It is the science of uncertainty, chance or likelihood (Cooper & Schindler, 2008). There are three kinds of probability; classical, empirical and subjective. In this instance, we will focus on a mixture of empirical probability which is based on past experiences and subjective probability which a probability is assigned to an event based upon whatever evidence is available. A closer look will be taken at the records of the patients treated by the emergency care team in the last six months along with tracking the cases seen in the emergency room over the next six months. At the conclusion of this study...
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...Unit 2 DB Subjective Probability “ A probability derived from an individual's personal judgment about whether a specific outcome is likely to occur. Subjective probabilities contain no formal calculations and only reflect the subject's opinions and past experience.” (investopedia.com, 2013) There are three elements of a probability which combine to equal a result. There is the experiment ,the sample space and the event (Editorial board, 2012). In this case the class is the experiment because the process of attempting it will result in a grade which could vary from an A to F. The different grades that can be achieved in the class are the sample space. The event or outcome is the grade that will be received at the end of the experiment. I would like to achieve an “A” in this class but due to my lack of experience in statistical analysis, my hesitation towards advanced mathematics, and the length of time it takes for me to complete my course work a C in this class may be my best result. I have a 1/9 chance or probability to receive an “A” in the data range presented to me which is (A,A-,B,B-,C,C-,D,D- AND F). By the grades that have been posted I would say that the other students have a much better chance of receiving a better grade than mine. I have personally use subjective probability in my security guard business in bidding on contracts based on the clients involved , the rates that I charge versus the rates other companies charge and the amount of work involved...
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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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