...* Definition of overconfidence In business or trading, an overestimation of one's abilities and of the precision of one's forecasts. Overconfident people set overly narrow confidence intervals in making predictions. They tend to overweigh their own forecasts relative to those of others. The self-serving attribution bias, under which individuals attribute past successes to their own skills and past failures to bad luck, can lead to overconfidence. In the context of financial markets, the confidence of a self-attributing investor increases when public information is in line with his or her forecast, but it does not decrease as much when public information contradicts his or her forecast. The investor therefore gains excessive confidence over time, after receiving different confirming and disconfirming public news. A similar cognitive bias, illusory superiority (or the above average effect), also causes people to overestimate their own abilities. Evidence of this bias is documented in studies that ask subjects to assess their abilities - indeed, a vast majority of people say they are above the average. * Hindsight bias Hindsight bias, also known as the knew-it-all-along effect or creeping determinism, is the inclination, after an event has occurred, to see the event as having been predictable, despite there having been little or no objective basis for predicting it, prior to its occurrence. It is a multifaceted phenomenon that can affect different stages of designs, processes...
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...Poo Randomness means lack of pattern or predictability in events.[1] Randomness suggests a non-order or non-coherence in a sequence of symbols or steps, such that there is no intelligible pattern or combination. Applied usage in science, mathematics and statistics recognizes a lack of predictability when referring to randomness, but admits regularities in the occurrences of events whose outcomes are not certain. For example, when throwing two dice and counting the total, we can say that a sum of 7 will randomly occur twice as often as 4. This view, where randomness simply refers to situations where the certainty of the outcome is at issue, applies to concepts of chance, probability, and information entropy. In these situations, randomness implies a measure of uncertainty, and notions of haphazardness are irrelevant. The fields of mathematics, probability, and statistics use formal definitions of randomness. In statistics, a random variable is an assignment of a numerical value to each possible outcome of an event space. This association facilitates the identification and the calculation of probabilities of the events. A random process is a sequence of random variables describing a process whose outcomes do not follow a deterministic pattern, but follow an evolution described by probability distributions. These and other constructs are extremely useful in probability theory. Randomness is often used in statistics to signify well-defined statistical properties. Monte Carlo methods...
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...David Chen Instructor Lyle Crawford Philosophy 100 Words: 1404 4th April 2013 A Brief Introduction of Libertarianism and Its Dilemma Do all of our actions have a cause, and are we merely a functioning object following determinism? Or do we control our own behaviours, so we have free will? This long time argument has been extended into two opponent theories: Libertarianism and Hard Determinism. Both of these theories, who are fans of incompatibilism, indicate determinism and free will cannot exist at the same time. One the contrary, the compatibilist theory, Soft Determinism, asserts that determinism and free will can be consistent. As believers and defenders of free will, even though libertarians seem to have strong appeals with our common sense, many of them have a problem defining what freedom is. Some libertarians try to come up with a major argument, agent causation, to reject Determinism. But the argument faces its own dilemma. Since Libertarianism has many problems which do not seem to have any solution, I prefer to choose the position of Hard Determinism in this paper. The first appeal of Libertarianism, which aims to convince people to believe in free will, claims that people are so particular that they are detached from other things. No laws can control people’s behaviours, and therefore “they are free”. Regardless humans have souls or not, we are still the controller of our own behaviours (Conee and Sider, 2005, p.119)....
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...Esther Puray I. Introduction A. Background A.1. The capacity of human beings to think rationally makes them question the existence of beings which leads to the concept of atheism. A.2. What is Atheism? A.3. One example of an atheist is Ram Samudrala. A.4. Who is Ram Samudrala? B. Issue B.1. Is the existence of god meaningful or meaningless? B.2. The theists say that god’s existence is meaningful because there would be nothing now; no motion and no existence, since he is the primary cause of all things and the primary mover. B.3. The atheists say that god’s existence is meaningless because believing in the existence of a god would be irrelevant since if this god, whom we assume that has free will, also gave us the same free will, then humans would just comply to his knowledge of the future thus humans’ free will contradicts an omniscient god or an all knowing god and from this, we can say that god is dead. C. Thesis Statement Therefore, the question of god is meaningless because humans have free will so their decisions are independent of god, and that he creates or promotes conflict. II. Body A. Argument 1: Humans have free will so their decisions are independent of god A.1. Introduction - Definition and concept of free will: capacity of rational agents to choose a course of action from among various alternatives 1. God created a universe, which is random a) Randomness is a requirement for free will b) Life and universe...
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...Random numbers in C++ and The Pythagorean Theorem Name Course Date Random numbers in C++ and The Pythagorean Theorem Introduction Computer programs in light of the technological advances that have been made, arguably make up for the most important concepts in such developments. A set of instructions designed to assist a computer to prefer a given task is referred to as a computer program. There are numerous languages used to create/design computer for instance Java Script, Java, C++, SQL and Sage (Laine, 2013). Computer programming is defined as a process of developing a working set of computer instructions meant to aid the computer in the performance of a given task. Computer programming starts with the formulation of a valid computer problem. This process is then followed by the development of an executable computer program, for instance Firefox Web Brower (Laine 2013). It is worth noting that there are other programs in the same realm. Computer programming is a diverse field that is of utmost importance in the modern world, especially with the continuous expansion of the internet. Perhaps the relevance of this can be underlined by the fact that computer programming has carved out as a course on itself. Computer programming is offered under several courses studied in colleges and universities (Laine, 2013). Computer programming is not only for computer students but for all who use computers on a day to day basis. This is by extension everyone since the...
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...Andrew R. Cohen1, Christopher Bjornsson1, Ying Chen1, Gary Banker2, Ena Ladi3, Ellen Robey3, Sally Temple4, and Badrinath Roysam1 1 Rensselaer Polytechnic Institute, Troy, NY 12180, USA, 2 Oregon Health & Science University, 3181 SW Sam Jackson Park Road, L606, Portland, OR 97239, USA 3 University of California, Berkeley, Berkeley, CA 94720, USA 4 Center for Neuropharmacology & Neuroscience, Albany Medical College, Albany, NY 12208, USA ABSTRACT An algorithmic information theoretic method is presented for object-level summarization of meaningful changes in image sequences. Object extraction and tracking data are represented as an attributed tracking graph (ATG), whose connected subgraphs are compared using an adaptive information distance measure, aided by a closed-form multi-dimensional quantization. The summary is the clustering result and feature subset that maximize the gap statistic. The notion of meaningful summarization is captured by using the gap statistic to estimate the randomness deficiency from algorithmic statistics. When applied to movies of cultured neural progenitor cells, it correctly distinguished neurons from progenitors without requiring the use of a fixative stain. When analyzing intra-cellular molecular transport in cultured neurons undergoing axon specification, it automatically confirmed the role of kinesins in axon specification. Finally, it was able to differentiate wild type from genetically modified thymocyte cells. Index Terms: Algorithmic information...
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...Stats/Modelling Notes Introduction & Summary Computer system users, administrators, and designers usually have a goal of highest performance at lowest cost. Modeling and simulation of system design trade off is good preparation for design and engineering decisions in real world jobs. In this Web site we study computer systems modeling and simulation. We need a proper knowledge of both the techniques of simulation modeling and the simulated systems themselves. The scenario described above is but one situation where computer simulation can be effectively used. In addition to its use as a tool to better understand and optimize performance and/or reliability of systems, simulation is also extensively used to verify the correctness of designs. Most if not all digital integrated circuits manufactured today are first extensively simulated before they are manufactured to identify and correct design errors. Simulation early in the design cycle is important because the cost to repair mistakes increases dramatically the later in the product life cycle that the error is detected. Another important application of simulation is in developing "virtual environments" , e.g., for training. Analogous to the holodeck in the popular science-fiction television program Star Trek, simulations generate dynamic environments with which users can interact "as if they were really there." Such simulations are used extensively today to train military personnel for battlefield situations, at a fraction...
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...Simulation Using RiskSim 9 9.1 RISKSIM OVERVIEW RiskSim is a Monte Carlo Simulation add-in for Microsoft Excel (Excel 97 and later versions) for Windows and Macintosh. RiskSim provides random number generator functions as inputs for your model, automates Monte Carlo simulation, and creates charts. Your spreadsheet model may include various uncontrollable uncertainties as input assumptions (e.g., demand for a new product, uncertain variable cost of production, competitor reaction), and you can use simulation to determine the uncertainty associated with the model's output (e.g., annual profit). RiskSim automates the simulation by trying hundreds of what-ifs consistent with your assessment of the uncertainties. To use RiskSim, you (1) create a spreadsheet model (2) optionally use SensIt to identify critical inputs (3) enter one of RiskSim's twelve random number generator functions in each input cell of your model (4) choose Tools | Risk Simulation from Excel's menu (5) specify the model output cell and the number of what-if trials (6) interpret RiskSim's histogram and cumulative distribution charts. RiskSim facilitates Monte Carlo simulation by providing: Twelve random number generator functions Ability to set the seed for random number generation Automatic repeated sampling for simulation Frequency distribution of simulation results Histogram and cumulative distribution charts All of RiskSim’s functionality, including its built-in...
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...Stata Guide (Version 10) Sunaina Dhingra This guide introduces the basic commands of Stata. 1. Starting Stata Start Stata by using shortcut on the desktop that you can double-click Start Stata using the Windows menu, click the Start > All Programs > Stata 10 Locate a Stata data file, with *.dta extension, and double-click 2. Stata environment Command—this is where Stata command are typed Results—output from commands, and error messages, appear here Review—a listing of commands recently executed Variables—names of variables in data and labels (if created) 3. Recording Output a. Log file Log file keeps track of everything that happens in the result window. In short, it keeps a record of the commands you have issued and their results during your session. In STATA log files have the extension .smcl or .log Go to File > Log > Begin to open a log file. A screen will pop up, asking for where you want the log file to be saved. Use command: log using filename [, append replace text] where filename is any name you wish to give the file. The append option simply adds more information to an existing file, whereas the replace option erases anything that was already in the file. Full logs are recorded in one of two formats: SMCL (Stata Markup and Control Language) or text (meaning ASCII). The default is SMCL, but the option text can change that. If you want to temporarily turn off the log session, type log off in the command window. The session will resume...
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...CHAPTER ONE 1.1 INTRODUCTION A casual look at the published empirical work in business and econometric will reveal that many economic relationships are of single –equation type. In such models, one variable (the dependent variable Y) is expressed as a linear function of one or more other variables (the explanatory variables, the X’s). An implicit assumption is that the cause and effect relationship, if any , between Y and X’s is unidirectional. The explanatory variables are the cause and the dependent variable is the effect . However, there are situations where there is a two- way or simultaneous relationships between Y and some of the X’s which makes the distinction between the dependent and the explanatory variables of dubious value. It is better to lump together a set of variables that can be determined simultaneously by the remaining set of variables- precisely what is done in simultaneous equation models. In such models, there is more than one equation - one for each of the mutually or jointly dependent or endogenous variables. And unlike the single equation models, in the simultaneous equation models, one may estimate the parameters of a single equation without taking into account information provided by the other equation in the system. In a simultaneous equation system, variables that appear only on the right – hand side of the equation are called exogenous or predetermined variables. They are truly independent or non-stochastic because they remain fixed. Variables...
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...How We Know What Isn't So The Fallibility of Human Reason in Everyday Life Thomas Gilovich THE FREE PRESS A Division of Macmillan, Inc. NEW YORK To Karen and liana Contents Acknowledgments 1. Introduction vn 1 PART ONE Cognitive Determinants of Questionable Beliefs 2. Something Out of Nothing: The Misperception and Misinterpretation of Random Data 3. Too Much from Too Little: The Misinterpretation of Incomplete and Unrepresentative Data 4. Seeing What We Expect to See: The Biased Evaluation of Ambiguous and Inconsistent Data 9 29 49 PART TWO Motivational and Social Determinants of Questionable Beliefs 5. Seeing What We Want to See: Motivational Determinants of Belief 6. Believing What We are Told: The Biasing Effects of Secondhand Information 7. The Imagined Agreement of Others: Exaggerated Impressions of Social Support 75 88 112 Contents PART THREE Examples of Questionable and Erroneous Beliefs 8. Belief in Ineffective "Alternative" Health Practices 9. Belief in the Effectiveness of Questionable Interpersonal Strategies 10. Belief in ESP 125 146 Acknowledgments 156 PART FOUR Where Do We Go from Here? 11. Challenging Dubious Beliefs: The Role of Social Science Notes Index 185 195 214 Four people made unusually significant contributions to this work and deserve special thanks. Lee Ross commented on drafts of many of the chapters and provided a number of his uniquely...
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...Additional information, including supplemental material and rights and permission policies, is available at http://ite.pubs.informs.org. Vol. 9, No. 1, September 2008, pp. 1–9 issn 1532-0545 08 0901 0001 informs ® doi 10.1287/ited.1080.0014 © 2008 INFORMS INFORMS Transactions on Education Using Simulation to Model Customer Behavior in the Context of Customer Lifetime Value Estimation Shahid Ansari, Alfred J. Nanni Accounting and Law Division, Babson College, Wellesley, Massachusetts 02457 {sansari@babson.edu, nanni@babson.edu} Dessislava A. Pachamanova, David P. Kopcso Mathematics and Science Division, Babson College, Wellesley, Massachusetts 02457 {dpachamanova@babson.edu, kopcso@babson.edu} T his article illustrates how simulation can be used in the classroom for modeling customer behavior in the context of customer lifetime value estimation. Operations research instructors could use this exercise to introduce multiperiod spreadsheet simulation models in a business setting that is of great importance in practice, and the simulation approach to teaching this subject could be of interest also to marketing and accounting instructors. At Babson College, the spreadsheet simulation exercise is part of an integrated one-case teaching day of the marketing, accounting, and operations research disciplines in the full-time MBA program, but the exercise is directly transferable to stand-alone courses as well. In our experience, students have...
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...18% and a standard deviation of 4% (see item (e) of Exhibit 8). The impact of fluctuations in foreign currency was estimated based on the current rate of 1.514 $/Pound and a standard deviation of 0.17 (see instruction for Part II, first bullet, item 3). We used a random number generator to determine the fluctuations from year to year and then calculated the percentage change year over year. The percentage fluctuation was applied to the calculated ROA to determine what the EBIT would be including potential foreign currency fluctuations. Taxes were estimated to be 27% based on the facts in the case. Once we calculated the net profits, we then estimated regular dividends paid each year. Based upon the cash flow statements in Exhibit 1, Diageo was paying approximately 35% of the operating income out as regular dividends each year. We used the same estimated rate of dividend payments for each period. Interest Coverage was calculated each year based the calculated EBIT and interest payments. When the interest rate coverage exceeded 8 (Diageo aimed to...
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... Something which simulate a system or environment in order to predict actual behavior . OR The process of simulating . Sentences of Simulation : 1. This exercise is the simulation of actual battle condition. 2. The most reliable simulation predicts that Hurricane will turn north . 3. Despite extensive simulation in the design phase, the aircraft fail to behave as expected. Definition: A simulation is the imitation of some real thing, state of affairs or process. The act of simulation something generally entales representing certain key characteristics or behaviors of a selected physical or abstract system. simulation refers to any analytical method to imitate a real life system, specially when other analysis or too mathematically complex or too difficult to reproduce. “simulation is a numerical technique for conducting experiments that involve certain types of mathematical & logical relationship, necessary to describe the behavior & structure of a complex real world system over extended period of time”. Simulation is a statistical experiment, hence its output must be interpreted by appropriate statistical tests. It is a most widely used management science technique for a imitation of reality. Simulation model : 1. Deterministic model In this model input & output variables are not permitted to be random variables. These models are described by exact functional relationship. 2. Probabilistic...
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...This pack of MTH 157 Final Exam includes answers to the next questions: 1. Write a short paragraph describing what is illustrated by the given display. 2. Identify the misuse or misrepresentation of statistics. 3. Kevin asked some of his friends how many hours they had worked during the previous week at their after-school jobs. The results are shown below. 4. Explain why having a strong linear correlation does not imply causality. Give an example to support your answer. 5. What is the expected height range for a 2-year old child? 6. Over the past two weeks, Jane earned $292 and $193 respectively, at her part time job. What must she earn in the third week to bring her three-week average earnings to $200 per week? 7. If the 26 is replaced with 39, how will this affect the range? How will this affect the standard deviation? How does this illustrate one advantage of the standard deviation over the range as a measure of spread? 8. Suppose that you want to select the game giving the highest average output over a long period of time. Which machine would you select? Why? 9. Consider a bowl containing 36 different slips of paper. Ten of the slips of paper each contain one of the digits from the set 0 through 9 and 26 slips each contain one of the 26 letters of the alphabet. If one slip is drawn at random, what is P(slip contains a letter formed from straight-line segments only)? 10. How many different sequences of 4 digits are possible if the first digit must be 3, 4, or 5 and...
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