Grinstead and Snell's Introduction to Probability

Grinstead and Snell's Introduction to Probability

Introductory probability course

36
Pages
0
Questions
709
Exercises
Discrete Probability Distributions
Simulation of Discrete Probabilities
Discrete Probability Distributions
Continuous Probability Densities
Simulation of Continuous Probabilities
Continuous Density Functions
Combinatorics
Permutations
Combinations
Card Shuffling
Conditional Probability
Discrete Conditional Probability
Continuous Conditional Probability
Paradoxes
Distributions and Densities
Important Distributions
Important Densities
Expected Value and Variance
Expected Value of Discrete Random Variables
Variance of Discrete Random Variables
Continuous Random Variables
Sums of Independent Random Variables
Sums of Discrete Random Variables
Sums of Continuous Random Variables
Law of Large Numbers
Law of Large Numbers for Discrete Random Variables
Law of Large Numbers for Continuous Random Variables
Central Limit Theorem
Central Limit Theorem for Bernoulli Trials
Central Limit Theorem for Discrete Independent Trials
Central Limit Theorem for Continuous Independent Trials
Generating Functions
Generating Functions for Discrete Distributions
Branching Processes
Generating Functions for Continuous Densities
Markov Chains
Introduction
Absorbing Markov Chains
Ergodic Markov Chains
Fundamental Limit Theorem for Regular Chains
Mean First Passage Time for Ergodic Chains
Random Walks
Random Walks in Euclidean Space
Gambler's Ruin
Arc Sine Laws
Appendices
Appendix A
Appendix B
Appendix C
Created 9 June 2024