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Six Ways Coding Teaches Math

Gambar
Last week I attended the Computer-Based Mathematics Education Summit in New York City, run by Wolfram Research and hosted at UNICEF headquarters. The motivation behind the summit is explained by Conrad Wolfram in this TED talk.  His idea is that mathematical modeling almost always involves these steps: Posing the right question. Taking a real world problem and expressing it in a mathematical formulation. Computation. Mapping the math formulation back to the real world. Wolfram points out that most math classes spend all of their time on step 3, and no time on steps 1, 2, and 4.  But step 3 is exactly what computers are good at, and what humans are bad at.  And furthermore, steps 1, 2, and 4 are important, and hard, and can only be done by humans (at least for now). So he claims, and I agree, that we should be spending 80% of the time in math classes on steps 1, 2, and 4, and only 20% on computation, which should be done primarily using computers. When I ...

Bayesian statistics in Montreal

I am happy to announce that I will be offering my tutorial, "Bayesian Statistics Made Simple" at PyCon 2014 in Montreal.  The tutorial is based on material from Think Bayes .  It includes some of the examples and exercises in the book.  Participants will work on examples during the workshop, so it should be engaging and reasonably fun.  This is the third time I have done the tutorial at PyCon. You can get more information about my tutorial (and the other tutorials at PyCon). And here is the description: Thursday 10 April 1:20 p.m.–4:40 p.m. Bayesian statistics made simple Allen Downey Audience level: Intermediate Category: Science Description An introduction to Bayesian statistics using Python.  Bayesian statistics are usually presented mathematically, but many of the ideas are easier to understand computationally.  People who know Python can get started quickly and use Bayesian analysis to solve real problems.  This tutorial is bas...

Freshman hordes slightly more godless than ever

Gambar
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 that the trend would continue, and that the students starting college in 2013 would again, be the most godless ever.  It turns out I was right -- just barely.  The number of students reporting no religious preference increased to 24.6%, slightly higher than the previous record, 24.5% in 2011.  Of course, that "difference" is not statistically meaningful.  More valid conclusions are 1) This year's data point is consistent with previous predictions, and 2) Data since 1990 support the conclusion that the number of incoming college students with no religious preference is increasing and probably accelerating. This analysis is based on survey results from the  Coo...

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

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 things Prof. Beazley does with Python generators. Normally O'Reilly provides 25 copies of the book for signing, but due to a mix up, they brought extra copies of all of my books, so I ended up signing about 50 books.  That was fun, but tiring. Several people asked me what I am working on now, so I thought I would answer here: 1) This semester I am revising Think Stats and using it to teach Data Science at Olin College.   Think Stats was the first book in the Think X series to get published.  There are still many parts I am proud of, but a few parts that make me cringe.  So I am fixing some errors and adding new sections on multiple linear regression, logistic regression, and s...

One step closer to a two-hour marathon

Gambar
This past Sunday Wilson Kipsang ran the Berlin Marathon in 2:03:23, shaving 15 seconds off the world record.  That means it's time to check in on the world record progression and update my article from two years ago.  The following is a revised version of that article, including the new data point. Abstract: I propose a model that explains why world record progressions in running speed are improving linearly, and should continue as long as the population of potential runners grows exponentially.  Based on recent marathon world records, I extrapolate that we will break the two-hour barrier in 2043. ----- Let me start with the punchline: The blue points show the progression of marathon records since 1970, including Wilson Kipsang's new mark.  The blue line is a least-squares fit to the data, and the red line is the target pace for a two-hour marathon, 13.1 mph.  The blue line hits the target pace in 2043. In general, linear extrapolation of a time seri...