...Course outline for MBA (PT) Course name: Statistics Analysis for Business Decisions | Course Code: | Term: Trimester I (Operations Management & Decision Science) | Course Objective:To familiarize the participants on the following: (a) Descriptive Statistics - Concepts / Applications(b) Inferential Statistics – Concepts / Applications(c) Scope and Limitation of Use | Evaluation Criteria: Mid Term Test: 30 marks Test 2 / Quiz: 10 marks Test 3 / Quiz: 10 marks End Term Exam: 50 marks | Faculty: Prof. (Dr.) Tohid Kachwala (email contact tkachwala@nmims.edu, Cabin number: 729, Mobile: 9869166393, Extension: 5871) | Pedagogy: 1. Use of problem solving for all the topics. 2. Use of Statistics in Practice / Case lets / Case studies. 3. Use of Software like Excel / SPSS. | Session Outline: | Session | Topic / Description | 1 | Introduction to Probability – Experiments, Assigning Probabilities, Some basic relationships of Probability Read ASW Chapter 4 or LR Chapter 4 | 2 | Theories of Probability - Classical theory, Relative Frequency theory, Axioms, Addition rule, Multiplication rule, Rule of at least one, Concept of Expected number of Success – Numerical Problems & Applications Case Problem: Hamilton County JudgesSIP: Morton International - Chicago, Illinois Read ASW Chapter 4 or LR Chapter 4 | 3 | Bayes Theorem – Theory, Problems & Applications, Probability revision using tabular...
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...Paper Presented to: Edmar Orata Probability by: Jirolyn Fabro Miguel Angelo Rosales March 15, 2012 I - Introduction II - Interpretations III - Etymology IV - History V - Applications 1. Weather Forecasting 2. Batting Average 3. Winning the Lottery 4. VI - Discussion VII - I-Introduction Probability is the ratio of the number of ways an event can occur to the number of possible outcomes. Probability is expressed as a fraction or decimal from 0 to 1. Probability is ordinarily used to describe an attitude of mind towards some proposition of whose truth we are not certain.[1] The proposition of interest is usually of the form "Will a specific event occur?" The attitude of mind is of the form "How certain are we that the event will occur?" The certainty we adopt can be described in terms of a numerical measure and this number, between 0 and 1, we call probability. [2] The higher the probability of an event, the more certain we are that the event will occur. Thus, probability in an applied sense is a measure of the likeliness that a (random) event will occur. The concept has been given an axiomatic mathematical derivation in probability theory, which is used widely in such areas of study as mathematics, statistics, finance, gambling, science, artificial intelligence/machine learning and philosophy to, for example, draw inferences about the likeliness of events. Probability is used to describe the underlying mechanics...
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...plausible or statistical associations they have observed. 1. Not be appropriate in all situations (e.g., may have indeterminate applicability) Given these numerous sources of errors, most knowledge-based systems require the incorporation of some form of uncertainty management. When implementing some uncertainty scheme we must be concerned with three issues: 1. How to represent uncertain data 2. How to combine two or more pieces of uncertain data 3. How to draw inference using uncertain data We will introduce three ways of handling uncertainty: Probabilistic reasoning. Certainty factors Dempster-Shafer Theory 1. Classical Probability The oldest and best defined technique for managing uncertainty is based on classical probability theory. Let us start to review it by introducing some terms. Sample space: Consider an experiment whose outcome is not predictable with certainty in advance. However, although the outcome of the experiment will not be known in advance, let us suppose that the set of all possible outcomes is known. This set of all...
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...TEMPLATE PROBABILITY AND STATISTICS Draft By Paul Chege Version 19.0, 23rd March, 2007 C. TEMPLATE STRUCTURE I. INTRODUCTION 1. TITLE OF MODULE Probability and Statistics 2. PREREQUISITE COURSES OR KNOWLEDGE Secondary school statistics and probability. 3. TIME The total time for this module is 120 study hours. 4. MATERIAL Students should have access to the core readings specified later. Also, they will need a computer to gain full access to the core readings. Additionally, students should be able to install the computer software wxMaxima and use it to practice algebraic concepts. 5. MODULE RATIONALE Probability and Statistics, besides being a key area in the secondary schools’ teaching syllabuses, it forms an important background to advanced mathematics at tertiary level. Statistics is a fundamental area of Mathematics that is applied across many academic subjects and is useful in analysis in industrial production. The study of statistics produces statisticians that analyse raw data collected from the field to provide useful insights about a population. The statisticians provide governments and organizations with concrete backgrounds of a situation that helps managers in decision making. For example, rate of spread of diseases, rumours, bush fires, rainfall patterns, and population changes. On the other hand, the study of probability helps decision making in government agents...
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... 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 comes from consumers who make their decisions...
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...A. (Honours) Course Effective from the Session : 2009–2010 National University Syllabus for 4 years B. B. A. Honours Course Subject : Management Second Year (Honours) |Subject Code |Subject Title |Marks |Credit | | |Business Communication and Report Writing (In English) |100 |4 | | |Computer and Information Technology |100 |4 | | |Taxation in Bangladesh |100 |4 | | |Business Statistics (In English) |100 |4 | | |Macro Economics |100 |4 | | |Human Resource Management |100 |4 | | |Viva-Voce |100 |4 | | |Total = |700 |28 | |Course Code ...
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...Management Science Summary Definitions by Subject Game theory * Nash equilibrium * In game theory, the Nash equilibrium is a solution concept of a non-cooperative game involving two or more players, in which each player is assumed to know the equilibrium strategies of the other players, and no player has anything to gain by changing only their own strategy. If each player has chosen a strategy and no player can benefit by changing strategies while the other players keep theirs unchanged, then the current set of strategy choices and the corresponding payoffs constitute a Nash equilibrium. * Stated simply, Amy and Wili are in Nash equilibrium if Amy is making the best decision she can, taking into account Wili's decision, and Wili is making the best decision he can, taking into account Amy's decision. Likewise, a group of players are in Nash equilibrium if each one is making the best decision that he or she can, taking into account the decisions of the others. * Pareto efficiency * Pareto efficiency, or Pareto optimality, is a state of allocation of resources in which it is impossible to make any one individual better off without making at least one individual worse off. The term is named after Vilfredo Pareto (1848–1923), an Italian economist who used the concept in his studies of economic efficiency and income distribution.The concept has applications in academic fields such as economics and engineering. * Given an initial allocation of goods among...
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...Research Report Analysis 8 Illustrations 12 Conclusion 14 Bibliography 15 Availability Bias Availability bias is a human cognitive bias that causes us to overestimate probabilities of events associated with memorable or dramatic occurrences. A cognitive bias is a pattern of deviation in judgment that occurs in particular situations. A cognitive bias can also be explained as a flaw in judgment which is caused by memory, social attribution, and statistical errors. Since, memorable events are further magnified by coverage in the media; the bias is compounded on the society level. Two well-known examples would be estimations of the probability of plane accidents and the kidnap of children. Both events are quite rare, but the huge majority of the population outrageously overestimates their probability, and behaves accordingly. In reality, one is more likely to die from an auto accident than from a plane accident, and a child has a higher risk of dying in an accident than the risk of getting kidnapped. Availability bias is at the root of many other human biases and culture-level effects. Availability bias is a cognitive illusion. The availability biasis a mental shortcut that occurs when people make judgments about the probability of events by how easy it is to think of examples. The availability bias operates on the notion that, "if you can think of it, it must be important." The availability of consequences associated with an action is...
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...history, dating back to 3600 BC, games of chance and gambling have existed ("Introduction- Gambling and Probability"). Since their invention, people have tried to decipher ways to predict the outcome of such games, thus a need to determine the likelihood of winning in games such as these evolved. The method created to suit this need is known as probability theory. Probability theory has been developed over hundreds of years, and is used to predict possible outcomes and assist in daily life. Probability has been developed and studied over time, and has been formed into formulas and theories that allow it to be used in a myriad of applications. Probability theory is a very important aspect of mathematics, and through the development...
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...UNIVERSITY OF DELHI DELHI SCHOOL OF ECONOMICS DEPARTMENT OF ECONOMICS Minutes of Meeting Subject: B.A. (Hons) Economics, First Semester (2011) Course: 01 (Introductory Microeconomics) Date of Meeting: Monday 25th July 2011, 3:00 pm Venue: Department of Economics, Delhi School of Economics, University of Delhi Convenors: Dr. Shreekant Gupta and Dr. Ram Singh Attended by: 1. Mohini Aggarwal, Rajdhani College 2. Punam Tyagi, Kalindi College 3. Pooja Khanna, Daulat Ram College 4. Vishnu Kanta Purohit, Indraparstha College 5. Supritio Mishra, Shyam Lal College 6. Asha Tikku, Kamala Nehru College 7. Manjit Kaur, Shyama Prasad Mukherjee College 8. Anand Kumar, College of Vocational Studies 9. Rashmi Mittal, Dyal Singh College (Morning) 10. Ruchi Gupta, Dyal Singh College (Morning) 11. Basanti Nayak, Satyawati College (Morning) 12. Malabika Pal, Miranda House 13. Meeta Kumar, Miranda House 14. Leema Paliwal, St. Stephen’s College 15. N. Manichandra Singh, Ram Lal Anand College (Evening) 16. Abdul Rasheed Ch., Hindu College 17. Jayashree Sahoo, Lady Shri Ram College 18. Kakali Barua, Lady Shri Ram College The following texts were agreed upon: 1. N. Gregory Mankiw (2007), Economics: Principles and Applications, 4th edition, India edition by South-Western, a part of Cengage Learning, Cengage Learning India Private Limited, ISBN-13:978-81-315-0577-9 (hereafter Mankiw, 2007, 4e). 2. Karl E. Case and Ray C. Fair (2007), Principles of Economics, 8th edition, Pearson Education Inc., ISBN 81-317-1587-6...
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...lose their jobs shortly. At this moment of low spirits, Xavier, one of the senior partners whom Alain had always found remarkably candid, joined him for lunch. “Well, Alain, I’m sure you have heard rumours about the board meeting this morning. The future of the four of you was discussed and a decision was taken to release one of you. I can’t tell you who - the Chairman is writing to you all immediately. However, I can say that we were unable to make the decision on merit, so we made it at random. The Chairman took one of four cards, each of which had one of your names on the back!” “So, I have a one in four chance of being out of work after Christmas”, said Alain. He felt relieved, as he had thought the odds might be worse. “But of course you know definitely who it is”, he added. Alain felt he could leach rather more out of the partner. “Since we both know that at least two out of Belén, Carlos or Dawood will definitely have a job here next year, if you tell me the name of two of them who will keep their jobs, it will still leave me in the dark as to my own fate. It would be pleasant to contemplate over Christmas the two who will continue in their jobs. Clearly, I’m not going to be able to see any of them before the Chairman’s letters arrive. If all three are to keep their jobs, just choose two names at random to tell me.” Xavier thought about this for a...
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...Massachusetts Institute of Technology 6.042J/18.062J, Fall ’02: Mathematics for Computer Science Professor Albert Meyer and Dr. Radhika Nagpal Course Notes 10 November 4 revised November 6, 2002, 572 minutes Introduction to Probability 1 Probability Probability will be the topic for the rest of the term. Probability is one of the most important subjects in Mathematics and Computer Science. Most upper level Computer Science courses require probability in some form, especially in analysis of algorithms and data structures, but also in information theory, cryptography, control and systems theory, network design, artificial intelligence, and game theory. Probability also plays a key role in fields such as Physics, Biology, Economics and Medicine. There is a close relationship between Counting/Combinatorics and Probability. In many cases, the probability of an event is simply the fraction of possible outcomes that make up the event. So many of the rules we developed for finding the cardinality of finite sets carry over to Probability Theory. For example, we’ll apply an Inclusion-Exclusion principle for probabilities in some examples below. In principle, probability boils down to a few simple rules, but it remains a tricky subject because these rules often lead unintuitive conclusions. Using “common sense” reasoning about probabilistic questions is notoriously unreliable, as we’ll illustrate with many real-life examples. This reading is longer than usual . To keep things in bounds...
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...oday, the term "applied mathematics" is used in a broader sense. It includes the classical areas noted above as well as other areas that have become increasingly important in applications. Even fields such as number theory that are part of pure mathematics are now important in applications (such as cryptography), though they are not generally considered to be part of the field of applied mathematics per se. Sometimes, the term "applicable mathematics" is used to distinguish between the traditional applied mathematics that developed alongside physics and the many areas of mathematics that are applicable to real-world problems today. There is no consensus as to what the various branches of applied mathematics are. Such categorizations are made difficult by the way mathematics and science change over time, and also by the way universities organize departments, courses, and degrees. Many mathematicians distinguish between "applied mathematics," which is concerned with mathematical methods, and the "applications of mathematics" within science and engineering. A biologist using a population model and applying known mathematics would not be doingapplied mathematics, but rather using it; however, mathematical biologists have posed problems that have stimulated the growth of pure mathematics. Mathematicians such as Poincaré and Arnold deny the existence of "applied mathematics" and claim that there are only "applications of mathematics." Similarly, non-mathematicians blend applied mathematics...
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...Goldstein, Schneider, and Siegel, Prentice Hall, 1997 Introduction In any introductory mathematics course designed for non-mathematics majors, it is important for the student to understand and apply mathematical ideas in a variety of contexts. With the increased use of advanced software in all fields, it is also important for the student to effectively interact with the new technology. Our goal is to integrate these two objectives in a supplement for the text Finite Mathematics and Its Applications, by Goldstein, Schneider, and Siegel. The package consists of interactive tutorials and projects in an Excel workbook format. The software platform used is the Microsoft Excel 5.0 spreadsheet. It was chosen for the following reasons: • • • suited to applications encountered in a finite math course widespread use outside of academia ease of creating reports with a professional look Use of Excel 5.0 was put into effect in the author's sections of the Finite Mathematics II course in the Spring 1996 semester. It was expanded to cover the Finite Mathematics I course for the Fall semester of 1996. Using a combination of specially designed projects and tutorials, students are able to analyze data, draw conclusions, and present their analysis in a professional format. The mathematical and computer skills learned with such an approach is an asset that they can carry with them to other courses as well as to their future places of employment. 2 Scope of supplement The package is divided...
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...Gujarat Technological University Syllabus for New MBA Program effective from Academic Year 2011-12 MBA I Semester I Accounting for Managers (AFM) 1. Course Objective: The objective of the course is to acquaint the students with the language of Accounting and to develop in them the ability to evaluate and use accounting data as an aid to decision making. The main purpose is to assist the students in developing skills in problem solving and decision making in the financial area. Emphasis is laid on analysis and utilization of financial and accounting data for planning and control. 2. Course Duration: The course duration is of 36 sessions of 75 minutes each i.e. 45 hours. 3. Course Contents: Module No: Module Content No. of Sessions 70 Marks (External Evaluation) 17 I II Fundamentals of Accounting Basic understanding of accounting, Accounting Concepts, Conceptual framework of financial statements, Accounting Policies, Journal Entries and preparation of accounts - Trial Balance to Balance sheet and profit and loss Account, Recognition of Income and Expenses, Provisions, Contingent Liabilities Accounting Standards and Applicability: Disclosure of Accounting Policies (AS-1), Valuation of Inventories (AS-2), Depreciation Accounting (AS-6), Income Recognition & Accrual Income (AS-9), Accounting of Fixed Assets (AS-10), Accounting for Intangible Assets (AS-26), Accounting for Investments (AS-13), 7 7 17 III IV V Preparing and Understanding Financial Statements...
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