This workshop was given the Data Institute's 2019 Conference.
It will provide a hands-on introduction to computational statistics. The focus will be on the efficient simulation of probabilities and statistics, for example the outcomes of dice rolling or the results of an A/B test.
By the end of the workshop, you should be able to apply bootstrapping and permutation testing to solve applied Data Science problems.
A working knowledge of Python (e.g., create variables and functions) is required. There are no math, probability, or statistics prerequisites.
You'll be writing code during the workshop so please bring a laptop. All other materials and resources will be provided.
A faculty member at University of San Francisco's MS in Data Science proram.
We'll be using Jupyter Notebook to run the code. If you are unfamiliar with Jupyter Notebook, please check out a video tutorial here.
There are 3 ways to run the code in this repo:
- Launch Colab in your browser:
- Launch Binder in your browser:
- Download and run locally
