Probability Theory and Game of Chance Jingjing Xu April 24‚ 2012 I. INTRODUCTION Probability theory is the mathematical foundation of statistics‚ and it can be applied to many areas requiring large data analysis. Curiously‚ that the study on probability theory has its root in parlor games and gambling. In 17th century‚ dice gambling was a very common entertainment among the upper class. An
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Suppose we take a random sample of size 100 from a discrete distribution in this manner: A green die and a red die are thrown simultaneously 100 times and let Xi denote the sum of the spots on the two dice on the ith throw‚ i = 1‚ 2‚...100. Find the probability that the sample mean number of spots on the two dice is less than 7.5. n = 100 µ = 7 µ[pic] = 7 σ = 2.41 σ[pic] = 2.41 /[pic] |X |2 |3 |4
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Probable Probability; Rolling Dice Statistics is based upon based upon common sense and logic‚ in a complex data. Probability is just one of the many topics in statistical mathematics. It is used in our daily life‚ all over the world. Even games‚ require taking a chance and using probability to determine the predicted outcomes. Probability is the measure of how often a particular event will happen if something is done repeatedly‚ (596 Webster’s Dictionary). You cannot determine
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entire populace like weight‚ gender‚ color‚ religion‚ job types‚ etc. Sample Data surveying is also extremely cost effective opposed to surveying an entire population. In short‚ this form of Sample Data is‚ from my own opinion‚ nothing more than probability theories. Population Data On the other hand‚ Population Data is just that; a means or census aimed at providing Data specifically based on the demographics‚ collective distinctiveness of a populace‚ individualism‚ and the primary starting point
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of Hume’s (1748) An Enquiry Concerning Human Understanding. Namely‚ section six‚ Of Probability‚ and‚ section seven‚ Of the Idea of Necessary Connexion‚ focusing on the text’s key points. Hume starts section six by asserting that there is no such thing as chance in the world. Instead‚ it is our ignorance of the causes of events that lead us to believe in chance. Nevertheless‚ Hume posits that there is probability‚ that is‚ a greater chance of something taking place than a contrary. Here‚ Hume uses
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Probability and Statistics Research Project Name: Lakeisha M. Henderson ID: @02181956 Spring 2007 Abstract Table of Contents Principle Component Analysis (PCA) Definition .4 Uses of PCA 5 Illustrative Example of PCA 5 Method to Determine PCA ..6 Basic Analysis of Variance (ANOVA) Purpose and Definition of ANOVA 12 Illustrative Example of ANOVA
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Tutorial on Discrete Probability Distributions Tutorial on discrete probability distributions with examples and detailed solutions. ------------------------------------------------- Top of Form | Web | www.analyzemath.com | | Bottom of Form | | Let X be a random variable that takes the numerical values X1‚ X2‚ ...‚ Xn with probablities p(X1)‚ p(X2)‚ ...‚ p(Xn) respectively. A discrete probability distribution consists of the values of the random variable X and their corresponding
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Chapter 3 Probability Distributions 1. Based on recent records‚ the manager of a car painting center has determined the following probability distribution for the number of customers per day. Suppose the center has the capacity to serve two customers per day. |x |P(X = x) | |0 |0.05 | |1 |0.20 | |2 |0.30 | |3 |0.25 | |4 |0.15 | |5 |0.05 | a. What is the probability that one
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------------------------------------------------- ------------------------------------------------- Research Paper ------------------------------------------------- THE PROBABILITY OF FINANCIAL CRISIS IN THE USA IN 2012-2013 ------------------------------------------------- Ilias Habbasov ------------------------------------------------- ------------------------------------------------- BBA course submitted to Elżbieta Jendrych‚ PhD on 3 December 2012 Winter Semester 2012/2013
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Analyzing Marketing Problems and Cases HIGHLIGHT 1 A Case for Case Analysis Cases assist in bridging the gap between classroom learning and the so-called real world of marketing management. They provide us with an opportunity to develop‚ sharpen‚ and test our analytical skills at: -Assessing situations. -Sorting out arid organizing key information. -Asking the right questions. -Defining opportunities and problems. -Identifying and evaluating alternative courses of action. -Interpreting data. -Evaluating
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