Allen B. Downey

Allen B. Downey

Professor of Computer Science at Olin College

Boston, Massachusetts

Allen Downey is a Professor of Computer Science at Olin College of Engineering. He has taught at Wellesley College, Colby College and U.C. Berkeley. He has a Ph.D. in Computer Science from U.C. Berkeley and Master's and Bachelor's degrees from MIT.

Think Bayes Think Bayes
by Allen B. Downey
September 2013
Print: $29.99
Ebook: $24.99

Think Python Think Python
by Allen B. Downey
August 2012
Print: $44.99
Ebook: $38.99

Think Complexity Think Complexity
by Allen B. Downey
March 2012
Print: $39.99
Ebook: $33.99

Think Stats Think Stats
by Allen B. Downey
July 2011
Print: $29.99
Ebook: $24.99

Allen B. blogs at:

Yet another power-law tail, explained

June 04 2014

At the next Boston Python user group meeting, participants will present their solutions to a series of puzzles, posted here.  One of the puzzles lends itself to a solution that uses Python iterators, which is something I was planning to get more familiar with it.  So I took on this… read more

Implementing PMFs in Python

May 08 2014

Last year I gave a keynote talk at PyCon Taiwan called "Python Epistemology," and I wrote this blog article about it.  The video is here, but unfortunately the sound quality is poor.  In the talk, I demonstrate the use of a Counter, one of the data structures in Python's collections module;… read more

Bayes's theorem and logistic regression

May 08 2014

This week's post has more math than most, so I wrote in it LaTeX and translated it to HTML using HeVeA. Some of the formulas are not as pretty as they could be. If you prefer, you can read this… read more

Are your data normal? Hint: no.

May 02 2014

One of the frequently-asked questions over at the statistics subreddit (reddit.com/r/statistics) is how to test whether a dataset is drawn from a particular distribution, most often the normal distribution.There are standard tests for this sort of thing, many with double-barreled names like Anderson-Darling, Kolmogorov-Smirnov, Shapiro-Wilk, Ryan-Joiner, etc.But these tests are… read more

Inferring participation rates in service projects

April 21 2014

About a week ago I taught my tutorial, Bayesian Statistics Made Simple, at PyCon 2014 in Montreal.  My slides, the video, and all the code, are on this site.  The turnout was great.  We had a room full of enthusiastic Pythonistas who are now, if I was successful, enthusiastic Bayesians.Toward… read more

The Internet and religious affiliation

April 16 2014

A few weeks ago I published this paper on arXiv: "Religious affiliation, education and Internet use".  Regular readers of this blog will recognize this as the article I was writing about in July 2012, including this article.A few days ago, MIT Technology Review wrote about my paper: How the Internet Is… read more

Think X, Y and Z: What's in the pipeline?

April 12 2014

Greetings from PyCon 2014 in Montreal!  I did a book signing yesterday at the O'Reilly Media booth.  I had the pleasure of working side by side with David Beazley, who was signing copies of The Python Cookbook, now updated for Python 3 and, I assume, including all of the perverse… read more

Freshman hordes slightly more godless than ever

March 06 2014

This article is an update to my annual series on one of the most under-reported stories of the decade: the fraction of college freshmen who report no religious preference has tripled since 1985, from 8% to 24%, and the trend is accelerating.In last year's installment, I made the bold prediction… read more

Webcast: There's Only One Test
October 04, 2011
People working with real data are often confused about hypothesis testing and paralyzed by the number of tests and their requirements. In this webcast, Allen B. Downey, author of Think Stats, presents a framework for using simple simulations to estimate...

Webcast: Bayesian Statistics Made Simple
October 26, 2012
Join Allen Downey, author of Think Stats: Probability and Statistics for Programmers for an introduction to Bayesian statistics using Python. Bayesian statistical methods are becoming more common and more important, but there are not many resources to...

"This book is a quick and easy introduction to programming and to Python. It is among the clearest introductions to both topics that I have seen in a long time."
--Andrew Binstock, Dr. Dobbs

"The author does an excellent job talking about the different systems and programs that are used in this career. This would also be a great textbook if your in school learning what your doing in the programming field."
--Stephaine Szostak, cybertron reviews

"I highly recommend this text for a first course in Computer Science at both secondary and university levels. It is as its title suggests an introduction to Python for Thinkers."
--Ira Laefsky, Amazon.com

"If Professor Downey ever opens an online class for "Think Complexity" either synchronized or on UDemy I would sign up in a heartbeat."
--Eric Chou, Amazon.com

"This short but extremely exciting book is simultaneously an invitation to actively participate in what Stephen Wolfram has called "A New Kind of Science", and an introduction to "Data Structures" (what traditionally has been the second course in Computer Science) with an exciting new motivation."
--Ira Laefsky

"Think Complexity is not just another how-to-program-in-Python book."
--Si Dunn, Sagecreek Productions