Introduction To Probability For Computing

• A Little Bit Of Queueing Theory
• Applications Of Tail Bounds Confidence Intervals Balls And Bins
• Bayesian Statistical Inference
• Before We Start Some Mathematical Basics
• Classical Statistical Inference
• Common Discrete Random Variables
• Continuous Random Variables Joint Distributions
• Continuous Random Variables Single Distribution
• Discrete Time Markov Chains Finite State
• Discrete Time Markov Chains Infinite State
• Ergodicity For Finite State Discrete Time Markov Chains
• Estimators For Mean And Variance
• Event Driven Simulation
• Expectation
• Generating Random Variables For Simulation
• Hashing Algorithms
• Heavy Tails The Distributions Of Computing
• Laplace Transforms
• Las Vegas Randomized Algorithms
• Monte Carlo Randomized Algorithms
• Normal Distribution
• Preface And Contents
• Primality Testing
• Probability On Events
• Tail Bounds
• The Poisson Process
• Variance Higher Moments And Random Sums
• Z Transforms
• _Introduction To Probability For Computing