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CPS615 Foils -- set D: Statistics and Random Numbers (In preparation for Monte Carlo)

This CPS615 Module has an overview of Random Numbers and statistics at the level needed for clear discussion of Monte Carlo Integration

It starts with basic properties of Random Numbers and extensions to multiple random variables and concept of independencs

Derivation of non-uniform probability distribution is illustrated with Gaussian distribution

We discuss computer generation of random variables for both sequential and parallel machines

Table of Contents for CPS615 Foils -- set D: Statistics and Random Numbers (In preparation for Monte Carlo)

001 Lecture Stream 4
    CPS 615 -- Computational Science in
    Simulation Track
    Statistics and Random Numbers
    October 15, 1995
002 Abstract for Statistics and Random Numbers CPS615 Module 
003 Basic Properties of Random Numbers
004 Means and Standard Deviations
005 Multiple Random Variables -- Correlation and Independence
006 Generation of Random Numbers
007 Derivation of NonUniform Probability Distributions
008 Mean and Standard Deviation of a function of a Random Variable
009 The Gaussian Distribution 
010 Generation of Gaussian Distributions
011 How do computers get random numbers?  
012 Simple Random Number Generator 
013 More on Generation of Random Numbers Numerically
014 An Illustration of Dangers of Correlations!
015 Parallel Random Numbers
016 The Law of Large Numbers or the Central Limit Theorem.
017 Shapes of Probability Distributions in Central Limit Theorem
018 Central Limit Theorem for Functions
019 Error in Central Limit Averaging
020 Simpson and Trapezoidal Rule Integrations
021 Newton-Cotes and Iterated Rules
022 Gaussian and Monte Carlo Integration