Introduction to Probability R Simulations

These Jupyter notebooks include the exposition and R code from the R sections of Introduction to Probability, Second Edition, Blitzstein & Hwang.

If Python is preferred to R, see this repository.

The easiest way to view the notebooks is in Google Colab:

You can also clone this repository and view the notebooks locally.

Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
10_inequalities_and_limit_theorems.ipynb		10_inequalities_and_limit_theorems.ipynb
11_Markov_chains.ipynb		11_Markov_chains.ipynb
12_markov_chain_monte_carlo.ipynb		12_markov_chain_monte_carlo.ipynb
13_poisson_processes.ipynb		13_poisson_processes.ipynb
1_probability_and_counting.ipynb		1_probability_and_counting.ipynb
2_conditional_probability.ipynb		2_conditional_probability.ipynb
3_random_variables_and_their_distributions.ipynb		3_random_variables_and_their_distributions.ipynb
4_expectation.ipynb		4_expectation.ipynb
5_continuous_random_variables.ipynb		5_continuous_random_variables.ipynb
6_moments.ipynb		6_moments.ipynb
7_joint_distributions.ipynb		7_joint_distributions.ipynb
8_transformations.ipynb		8_transformations.ipynb
9_conditional_expectation.ipynb		9_conditional_expectation.ipynb
README.md		README.md

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