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

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
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 (
Background image of page 1
This is the end of the preview. Sign up to access the rest of the document.

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...
View Full Document

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.

Ask a homework question - tutors are online