Understanding Probability Theory With Exercises in R and Python

Formal probability theory is a rich and sophisticated field of mathematics that forms the foundation of statistics and data science. Unfortunately it also has reputation for being confusing, if not outright impenetrable.
Much of that intimidation, however, is due not to the abstract mathematics but rather how they are taught. Many introductions to probability theory confound the abstract mathematics with their practical implementations, convoluting what we can calculate in the theory with how we implement those calculations. To make matters even worse, probability theory is used to model a variety of subtlety different systems, which then burdens the already confused mathematics with the distinct and often conflicting philosophical connotations of those applications.

In this course we will attempt to untangle this pedagogical knot and illuminate the basic concepts and manipulations of probability theory and their applications. Our ultimate goal is to demystify what we can calculate in probability theory and how we can perform those calculations in practice, the latter being demonstrated with interactive exercises in R and Python.

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Speaker Bio

Michael Betancourt (https://betanalpha.github.io) is the principle research scientist at Symplectomorphic, LLC, where he develops theoretical and methodological tools to support practical Bayesian inference. He is also a core developer of Stan, where he implements and tests these tools. In addition to hosting tutorials and workshops on Bayesian inference with Stan he also collaborates on analyses in, amongst others, epidemiology, pharmacology, and physics.

Michael on Twitter: https://twitter.com/betanalpha

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Agenda

10:00 - 12:00 Lecture / workshop
12:00 - 01:00 Lunch
01:00 - 05:00 Lecture / workshop

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Requirements

The course will assume some familiarity with the basics of calculus and linear algebra.

In order to participate in the interactive exercises attendees must provide a laptop with R or Python. Some exercises will optionally utilize Stan and we suggest that you have the the latest version of RStan (https://cran.r-project.org/web/packages/rstan/index.html) or PyStan (https://pystan.readthedocs.io/en/latest/) installed. Please verify that you can run the 8schools model as discussed in the RStan Quick Start Guide (https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started) or the PyStan Quick Start Guide (https://pystan.readthedocs.io/en/latest/getting_started.html) and report any installation issues on the Stan Forums (https://discourse.mc-stan.org) as early as possible.

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POLICY

No refunds.

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CODE OF CONDUCT

WiMLDS is dedicated to providing a harassment-free experience for everyone. We do not tolerate harassment of participants in any form. All communication should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery is not appropriate.

Be kind to others. Do not insult or put down others. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate.

Thank you for helping make this a welcoming, friendly community for all. All attendees should read the full Code of Conduct before participating: https://github.com/WiMLDS/starter-kit/wiki/Code-of-conduct