Schedule for classes and class notes (pdf files):

Current version of notes (updated Mar 28, 2008)

Week
1	Intro, Sample Space, Events, Venn Diagram, Kolmogorov axioms, Probability Laws Conditional Probability, Independence
2	Tree diagrams, Total Probability Bayes Rule Counting Methods
3	Bernoulli expt, Random variables, probability mass function, cumulative distribution functions, Expectation, Variance,
4	Binomial distribution, (+ table) Geometric & Poisson distribution (+table)
5	2 random variable:Compound pmfs, covariance conditional distributions, Intro to continuous random variables, review for midterm 1
6	exam Continuous Random Variables, probability distribution functions, uniform distribution
7	Exponential distribution & properties, Erlang distribution Normal distribution and properties + Table
8	Normal distribution – probability calculations Central Limit Theorem (CLT), Multiple random variables,
9	Correlation, Covariance, Bivariate Normal Intro to stochastic processes, Bernoulli Process
10	Break
11	bernoulli Process Poisson Process
12	exam Poisson Process, Birth & Death Process
13	Birth & Death Process, Brownian Motion, Markov Chains -intro
14	Markov Chains –introduction –transition probabilities
15	Markov Chains- probability calculations Steady State Behavior, Absorptions
16	Repetition

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