Weekly links for December 30

What does randomness look like?, from Empirical Zeal.

Why you should hire an astronomer – much of this applies to other sciences as well.

Joshua Ganz on an application of game theory to parenting (of multiple children).

A re-analysis of Monopoly from Possibly Wrong.

Carl Bialik asks (passed on by Andrew Gelman at his blog) what do journalists do wrong in reporting studies? Gelman can’t think of an answer but commenters can.

Terry Tao wrote an introduction to special relativity for a high school math circle.

George Hart has a video on slicing the .

Maths is all around you, according to this not-actually-vintage episode of Look Around You. (Via Dan Meyer, @ddmeyer on twitter).

Ramanujan: Letters from an Indian Clerk, a documentary about Ramanujan.

Gregory Buck, The wondrous mathematics of winter.

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Weekly links for December 16

The first chapter of Howard Wainer’s book Picturing the Uncertain World, entitled “The Most Dangerous Equation”, is available from Princeton. (The equation in question is the fact that the standard deviation of the sampling distribution is the standard deviation of the population divided by the square root of sample size.

John Cook wrote sleeper theorems, theorems that one only comes to understand the importance of long after learning them; his list includes Bayes’ theorem and Jensen’s inequality.

In 1971, Laurence H. Tribe wrote an article in the Harvard Law Review, Trial by mathematics: precision and ritual in the legal process, on whether it was legitimate to use probability in trials.

The Museum of Mathematics opened yesterday in New York. New Scientist reports.

Nate Silver gave a talk at Google.

Coursera courses on data analysis

For those of you who want to learn R: videos from Roger Peng’s course “Computing for Data Analysis” are linked to at Revolution Analytics.

Roger Peng is a professor of Biostatistics at Johns Hopkins and one of the bloggers at Simply Statistics. The course has a trailer video, below:

The course itself is a short one, 4 weeks at 3-5 hours per week, and the next session of it starts on January 2, 2013.

Another course from a Hopkins professor and Simply Statistics blogger being offered on Coursera, starting January 22, is Jeff Leek’s Data Analysis:

Peng and Leek have written a blog psot on why they’re teaching MOOCs.

Steele’s genre list

J. Michael Steele is teaching Statistics 530 (first-semester graduate measure-theoretic probability) at Penn this semester. (I’ve taken classes from him, and I took this class, but he wasn’t teaching it.) Embedded in his course web page is an interesting aside on how mathematics gets done:

GRaVy: This stands for “Generalizations”, “Refinements” and “Variations” and this one word represents the way that 80% of day-to-day mathematics (and mathematical science, including statistics and computer science) gets created. The paradigm needs no modification in mathematical statistics, and the story for applied statistics requires only small modification.

This also includes an implicit list of “genres” of mathematical papers (which is incompletely written; I assume that this picks up on something said in class): the “Generalizations”, “Refinements” and “Variations” above, “Greenfield Projects”, “P+Q=R”, “synthesis” or “survey”, and the “Pollution Piece” (which pollutes the literature). What other genres are there?

Also from Steele: videos of ten lectures on “Probability Theory and Combinatorial Optimization” – I haven’t watched but I assume these are related to his little book of the same title, and I can’t resist linking to Steele’s random rants.