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
017
Discrete Probability Distributions
031
Continuous Probability Densities
Simulation of Continuous Probabilities
011
Continuous Density Functions
023
Combinatorics
Permutations
024
Combinations
040
Card Shuffling
05
Conditional Probability
Discrete Conditional Probability
063
Continuous Conditional Probability
014
Paradoxes
06
Distributions and Densities
Important Distributions
046
Important Densities
038
Expected Value and Variance
Expected Value of Discrete Random Variables
041
Variance of Discrete Random Variables
029
Continuous Random Variables
028
Sums of Independent Random Variables
Sums of Discrete Random Variables
011
Sums of Continuous Random Variables
021
Law of Large Numbers
Law of Large Numbers for Discrete Random Variables
017
Law of Large Numbers for Continuous Random Variables
018
Central Limit Theorem
Central Limit Theorem for Bernoulli Trials
018
Central Limit Theorem for Discrete Independent Trials
015
Central Limit Theorem for Continuous Independent Trials
015
Generating Functions
Generating Functions for Discrete Distributions
011
Branching Processes
08
Generating Functions for Continuous Densities
010
Markov Chains
Introduction
019
Absorbing Markov Chains
036
Ergodic Markov Chains
033
Fundamental Limit Theorem for Regular Chains
09
Mean First Passage Time for Ergodic Chains
024
Random Walks
Random Walks in Euclidean Space
015
Gambler's Ruin
011
Arc Sine Laws
02
Appendices
Appendix A
00
Appendix B
00
Appendix C
00
Created 9 June 2024