Spring 2008: CSE 221 Probabilistic Analysis of Computer Systems

Lecture 1 Course outline and schedule, Introduction, Event Algebra
Lecture 2 Probability axioms, Combinatorial problems.
Lecture 3 Conditional probability, Independent events, Bayes rule, Bernoulli trials
Lecture 4 Discrete random variables, Mass and distribution functions
Lecture 5 Special discrete distributions
Lecture 6 Special discrete distributions, Probability Generating Function
Lecture 7 Discrete random vectors, Independent random variables.
Lecture 8 Continuous random variables, Uniform and Normal distribution.
Lecture 9 Exponential distribution, Reliability and failure rate
Lecture 10 Expectation of random variables, Moments
Lecture 11 Multiple random variables, Transform methods
Lecture 12 Moments and transforms of special distributions
Lecture 13 Stochastic Processes
Lecture 14 Discrete time Markov chains
Lecture 15 Discrete time Markov chains
Lecture 16 Discrete time Markov chains
Lecture 17 Statistical inference
Lecture 18 Statistical Inference
Lecture 19 Statistical Inference
Lecture 20 Continuous Time Markov Chains
Lecture 21 Simple Queuing Models
Lecture 22 Availability Analysis