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Prob/Stats Understanding Probability: Chance Rules in Everyday Life by Tijms

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  1. Jan 21, 2013 #1

    micromass

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    Table of Contents:
    Code (Text):

    [LIST]
    [*] Preface
    [*] Introduction
    [*] Probability in Action
    [LIST]
    [*] Probability questions
    [*] The law of large numbers and simulation
    [LIST]
    [*] The law of large numbers for probabilities
    [*] Basic probability concepts
    [*] Expected value and the law of large numbers
    [*] The drunkard's walk
    [*] The St. Petersburg paradox
    [*] Roulette and the law of large numbers
    [*] The Kelly betting system
    [*] Random-number generator
    [*] Simulating from probability distributions
    [*] Problems
    [/LIST]
    [*] Probabilities in everyday life
    [LIST]
    [*] The birthday problem
    [*] The coupon collector's problem
    [*] Craps
    [*] Gambling systems for roulette
    [*] The 1970 draft lottery
    [*] Bootstrap method
    [*] Problems
    [/LIST]
    [*] Rare events and lotteries
    [LIST]
    [*] The binomial distribution
    [*] The Poisson distribution
    [*] The hypergeometric distribution
    [*] Problems
    [/LIST]
    [*] Probability and Statistics
    [LIST]
    [*] The normal curve
    [*] The concept of standard deviation
    [*] The square-root law
    [*] The central limit theorem
    [*] Graphical illustration of the central limit theorem
    [*] Statistical applications
    [*] Confidence intervals for simulations
    [*] The central limit theorem and random walks
    [*] Falsified data and Benford's law
    [*] The normal distribution strikes again
    [*] Statistics and probability theory
    [*] Problems
    [/LIST]
    [*] Chance trees and Bayes' rule
    [LIST]
    [*] The Monty Hall dilemma
    [*] The test paradox
    [*] Problems
    [/LIST]
    [/LIST]
    [*] Essentials of Probability
    [LIST]
    [*] Foundations of probability theory
    [LIST]
    [*] Probabilistic foundations
    [*] Compound chance experiments
    [*] Some basic rules
    [/LIST]
    [*] Conditional probability and Bayes
    [LIST]
    [*] Conditional probability
    [*] Bayes' rules in odds form
    [*] Bayesian statistics
    [/LIST]
    [*] Basic rules for discrete random variables
    [LIST]
    [*] Random variables
    [*] Expected value
    [*] Expected value of sums of random variables
    [*] Substitution rule and variance
    [*] Independence of random variables
    [*] Special discrete distributions
    [/LIST]
    [*] Continuous random variables
    [LIST]
    [*] Concept of probability density
    [*] Important probability densities
    [*] Transformation of random variables
    [*] Failure rate functions
    [/LIST]
    [*] Jointly distributed random variables
    [LIST]
    [*] Joint probability densities
    [*] Marginal probability densities
    [*] Transformation of random variables
    [*] Covariance and correlation coefficient
    [/LIST]
    [*] Multivariate normal distribution
    [LIST]
    [*] Bivariate normal distribution
    [*] Multivariate normal distribution
    [*] Multidimensional central limit theorem
    [*] The chi-square test
    [/LIST]
    [*] Conditional distributions
    [LIST]
    [*] Conditional probability densities
    [*] Law of conditional probabilities
    [*] Law of conditional expectations
    [/LIST]
    [*] Generating functions
    [LIST]
    [*] Generating functions
    [*] Moment-generating functions
    [/LIST]
    [*] Markov Chains
    [LIST]
    [*] Markov model
    [*] Transient analysis of Markov chains
    [*] Absorbing Markov chains
    [*] Long-run analysis of Markov chains
    [/LIST]
    [/LIST]
    [*] Appendix: Counting methods and [itex]e^x[/itex]
    [*] Recommended reading
    [*] Answers to odd-numbered problems
    [*] Bibliography
    [*] Index
    [/LIST]
     
     
    Last edited by a moderator: May 6, 2017
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