exam_1_sg_m4320_f2010_v1_0

exam_1_sg_m4320_f2010_v1_0 - e.g. the rst example on page...

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Exam 1 study guide: Math 4320 Fall 2010 1. Material: Chapters 1 and 2 (1) probability spaces, random variables (discrete random variables and random variables with pdfs) (2) major discrete distributions: Bernoulli, binomial, Poisson, hypergeometric (3) major continuous distributions: uniform, exponential, normal (4) expectation, variance, higher moments (define and compute) (5) joint distributions of random vectors, marginal distributions (6) conditional probability (7) conditional expectation (definition, properties, computations) (8) conditional distributions (discrete conditional distributions and conditional pdfs) (9) computing probabilities and means by conditioning (
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Unformatted text preview: e.g. the rst example on page 59 of Taylor and Karlin) (10) random sums (11) martingales (a) denition (b) show that a given stochastic process is a martingale (c) maximal inequality (12) Markov inequality 2. Material: Chapter 3 (1) denition of a Markov chain (2) transition probability matrices (a) computations with a given transition probability matrix (b) nd the transition probability matrix given a description of the model (3) classes of Markov chains (a) absorbing Markov chains (b) random walks (4) rst-step analysis (Exam 1 will contain at least 1 problem that requires rst-step analysis) 1...
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This note was uploaded on 10/03/2011 for the course MATH 3364 taught by Professor Staff during the Spring '08 term at University of Houston.

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