Report from SciPy 2019

Greetings from Austin and SciPy 2019. In this post, I’ve collected the materials for my tutorials and talks.

On Monday morning I presented Bayesian Statistics Made Simple in an extended 4-hour format:

Here are the slidesCode and Jupyter notebooks are in this repositorySetup instructions are here

In the afternoon I presented a tutorial on Complexity Science:

Here are the slidesCode and Jupyter notebooks are in this repositorySetup instructions are here

On Tuesday I presented a short talk for the teen track. Here are the slides, with links to the two notebooks on Binder:

Text analysis with Python (thanks, John Green)Game of Life implemented with NumPy

And tomorrow I’m presenting a talk, “Generational Changes in Support for Gun Laws: A Case Study in Computational Statistics”:

Abstract: In the United States, support for gun control has been declining among all age groups since 1990; among young adults, support is substantially lower than among previous generations. Using data from the General Social Survey (GSS), I perform age-period-cohort analysis to measure generational effects.
In this talk, I demonstrate a computational approach to statistics that replaces mathematical analysis with random simulation. Using Python and libraries like NumPy and StatsModels, we can define basic operations — like resampling, filling missing values, modeling, and prediction — and assemble them into a data analysis pipeline.

Here are the slidesAnd here’s the repository with the code and notebooks

If you are at SciPy, my talk is Thursday morning from 10:20 to 10:50 in the Zlotnik Ballroom.