I’m an assistant teaching professor of Statistics & Data Science at Carnegie Mellon University. I work on statistical models to understand and predict where events occur, while also helping lead the Teaching Statistics Group study how students learn statistics and how we can teach better.
You should read my book Statistics Done Wrong, the woefully complete guide to the many ways that statistics is abused in science. Now available in print, published by No Starch Press!
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You can contact me at email@example.com or find me in my office, Baker 232K.
I keep extensive online notebooks on random topics of interest to me. Some recent updates:
Causality – December 2, 2022
Regression – September 2, 2022
Dimensional analysis in statistics – August 4, 2022
Survey sampling – June 14, 2022
Algorithmic fairness – May 7, 2022
Algorithmic due process – May 7, 2022
Privacy and surveillance – March 13, 2022
The many-hands and many-causes problems – January 18, 2022
Machine learning and law – January 10, 2022
Statistical misconceptions – August 10, 2021
…and a bunch more.
Recent posts from the refsmmat report:
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- ScienceForums.net, one of the world’s largest online discussion forums focused on science and science news.
- The Regressomatic, an interactive demonstration of linear regression diagnostics.
- madman, a Python-based Mad Libs generator that uses Markov chains to generate rather alarming texts. Provide a perfectly sensible text file and madman makes it less sensible.
- seuss, a Python-based poetry generator that uses Markov chains to create humorous and surprising poems.