Monte Carlo Simulation and Resampling Methods
Simulation and resampling methods have been an essential set of contemporary statistical and computational techniques. The underlying logic of using randomness to solve problems also provides a more realistic understanding of the probabilistic interpretation of real-world events. In this workshop, we will cover a wide range of topics related to Monte Carlo simulation, from basic ideas of Monte Carlo methods, to reject sampling, simulating statistical models, and resampling techniques such as bootstrapping and cross validation, and implement them in programming languages. Some prior experience with basic programming and statistical methods will be expected.
[Google Colab] (GU login required)
Note: The data is self-contained with the Colab notebook.