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   1 -0_Set_up.html

   1 -Setting up.mp4

   2 -Setting up Jupyter Notebooks.mp4

   3 -Review.html

   3 -Table of Common Distributions.pdf

   4 -Introduction to Monte Carlo Methods.en_US.vtt

   4 -Introduction_ Monte Carlo Methods.pdf

   5 -nihms219206.pdf

     4 Intro to Bootstrap-script.R

     4_Intro_to_Bootstrap.html

      4 Bootstrap.ipynb

       prereqs.cpython-36.pyc

       4 Bootstrap-checkpoint.ipynb

     1 Introduction-script.R

     1_Introduction.html

      1 Introduction.ipynb

       1 Introduction-checkpoint.ipynb

     2 Generating Random Variables-script.R

     2_Generating_Random_Variables.html

      2 Generating Random Variables.ipynb

     3 Monte Carlo Integration-script.R

     3_Monte_Carlo_Integration.html

      3 Monte Carlo Integration.ipynb

     4 Controlling and Accelerating Convergence-script.R

     4_Controlling_and_Monitoring_Convergence.html

      4 Controlling and Accelerating Convergence.ipynb

       prereqs.cpython-36.pyc

       4 Controlling and Accelerating Convergence-checkpoint.ipynb

     5 MC EM Algorithm.Rmd

     5_MC_EM_Algorithm.html

      5 Monte Carlo EM.ipynb

       prereqs.cpython-36.pyc

       5 Monte Carlo EM-checkpoint.ipynb

     6 Intro to Markov Chains.Rmd

     6 Metropolis-Hastings-script.R

     6_Metropolis-Hastings_Algorithms.html

      6 Metropolis Hastings Algorithm.ipynb

       6 Metropolis Hastings Algorithm-checkpoint.ipynb

     7 Gibbs Sampler-script.R

     7_Gibbs_Samplers.html

      7 Gibbs Samplers.ipynb

       7 Gibbs Samplers-checkpoint.ipynb

      prereqs.cpython-36.pyc

     COMMIT_EDITMSG

     config

      applypatch-msg.sample

      post-update.sample

      pre-commit.sample

      pre-rebase.sample

      update.sample

      exclude

      HEAD

        master

         master

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       master

        master

   1 -2_Generating_Random_Variables.html

   1 -Uniform Random Variables.en_US.vtt

   2 -Transformation Methods.en_US.vtt

   3 -Inverse Transform Method.en_US.vtt

   4 -Accept-Reject Method.en_US.vtt

   1 -3_Monte_Carlo_Integration.html

   1 -Simple Monte Carlo Integration.en_US.vtt

   2 -Calculating Tail Probabilities.en_US.vtt

   3 -Importance Sampling.en_US.vtt

   4 -Importance Sampling Examples.en_US.vtt

   1 -4_Intro_to_Bootstrap.html

   1 -Intro to Bootstrap.mp4

   2 -Paired Bootstrap Example.mp4

   3 -4_Controlling_and_Monitoring_Convergence.html

   3 -Monitoring Convergence.mp4

   4 -Antithetic Variables.mp4

   5 -Exercise.mp4

   1 -Optimization with Simulated Annealing.en_US.vtt

   2 -06767727.pdf

   2 -Traveling Salesman Problem Simulated Annealing Solution.mp4

   3 -Genetic Algorithms.mp4

   4 -TSP Genetic Algorithm.mp4

   5 -TSP Genetic Algorithm with Crossover.mp4

   GA-TSP-Solution-Crossover.py

   Optimization - Genetic Algorithms.ipynb

   TSP GA Solution-Crossover.ipynb

   TSP Simulated Annealing Algorithm Solution.ipynb

   1 -5_MC_EM_Algorithm.html

   1 -EM Algorithm.mp4

   2 -Monte Carlo EM.en_US.vtt

   1 -6_Intro_to_Markov_Chains.html

   1 -Markov Chains part 1.en_US.vtt

   2 -Markov Chains part 2.en_US.vtt

   3 -6_Metropolis-Hastings_Algorithms.html

   3 -Metropolis Hastings algorithms.mp4

   4 -Bayesian Logistic Regression.en_US.vtt

   4 -Bayesian Reanalysis of the Challenger O-Ring Data.pdf

   4 -farawaychapt2.pdf

   1 -7_Gibbs_Samplers.html

   1 -Gibbs Sampler algorithm.mp4

   2 -Bayesian Change Point Analysis.en_US.vtt

   2 -Hierarchical Bayesian Analysis of changepoint problems bayes_changepoint_poisson_1.pdf

  Bonus Resources.txt