Formal probability theory is a rich & sophisticated field of mathematics that forms the foundation of statistics & 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 & often conflicting philosophical connotations of those applications.
In this course we will attempt to untangle this pedagogical knot & illuminate the basic concepts & manipulations of probability theory & their applications. Our ultimate goal is to demystify what we can calculate in probability theory & how we can perform those calculations in practice, the latter being demonstrated with interactive exercises in R & Python.
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Speaker Bio
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Michael Betancourt (https://betanalpha.github.io) is the principle research scientist at Symplectomorphic, where he develops theoretical & methodological tools to support practical Bayesian inference. He is also a core developer of Stan, where he implements & tests these tools. In addition to hosting tutorials & workshops on Bayesian inference with Stan he also collaborates on analyses in, amongst others, epidemiology, pharmacology, & physics.
Michael on Twitter: https://twitter.com/betanalpha
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Agenda
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10:00 - 12:00 Lecture / workshop
12:00 - 01:00 Lunch
01:00 - 05:00 Lecture / workshop
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Requirements
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The course will assume some familiarity with the basics of calculus & 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 & 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) & report any installation issues on the Stan Forums (https://discourse.mc-stan.org) as early as possible.
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POLICY
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No refunds.
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CODE OF CONDUCT
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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 & imagery is not appropriate.
Be kind to others. Do not insult or put down others. Behave professionally. Remember that harassment & 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
