Explore analyses of popular songs, or contribute an analysis of your own.

That a Facebook fans of "Barack Obama" might be Democrats or people who liked the "No H8" campaign were more likely to be gay seems obvious, but other correlations were far less intuitive. "Curly Fries" and "Thunderstorms" seem to be surprisingly linked with a high IQ, while "That Spider is More Scared Than U" happens to draw a non-smoking fan base. Predictors of male heterosexuality include "Being Confused After Waking Up From Naps." An appreciation of "Hello Kitty" tended to be associated with people who were more open and less emotionally stable. [Sounds like overtraining to me, but surely they wouldn't make such a fundamental mistake? Right?]

Many people who have managed projects with hours have a hard time understanding why story points are better. They have failed to understand some fundamental data that has been published for over 20 years in the industry literature as well as the latest research.

First, let's look at the latest data on project failures. Failure rates are increasing for IT projects during the current disruption of the global financial system. The latest Standish group analysis shows that agile projects have three times the success rate of traditional projects. Jim Johnson now recommends agile practice be used universally on all projects.

PROBLEM: You are a web programmer. You have users. Your users rate stuff on your site. You want to put the highest-rated stuff at the top and lowest-rated at the bottom. You need some sort of "score" to sort by.

...

CORRECT SOLUTION: Score = Lower bound of Wilson score confidence interval for a Bernoulli parameter.

For all of the other languages, the researchers discovered, the more data-dense the average syllable is, the fewer of those syllables had to be spoken per second — and the slower the speech thus was. English, with a high information density of .91, is spoken at an average rate of 6.19 syllables per second. Mandarin, which topped the density list at .94, was the spoken slowpoke at 5.18 syllables per second. Spanish, with a low-density .63, rips along at a syllable-per-second velocity of 7.82. The true speed demon of the group, however, was Japanese, which edges past Spanish at 7.84, thanks to its low density of .49. Despite those differences, at the end of, say, a minute of speech, all of the languages would have conveyed more or less identical amounts of information.

Wind power proponent and author Paul Gipe estimated in Wind Energy Comes of Age that the mortality rate for wind power from 1980–1994 was 0.4 deaths per terawatt-hour. Paul Gipe's estimate as of end 2000 was 0.15 deaths per TWh, a decline attributed to greater total cumulative generation.

Hydroelectric power was found to to have a fatality rate of 0.10 per TWh (883 fatalities for every TW·yr) in the period 1969–1996

Nuclear power is about 0.04 deaths/TWh.

Given our development processes we found the average productivity of a single Django developer to be equivalent to the output generated by two C# ASP.NET developers. Given equal-sized teams, Django allowed our developers to be twice as productive as our ASP.NET team.

I suspect these results may actually reflect a lower bound of the productivity differences. It should be noted that about half of the Team Python developers, while fluent in Python, had not used Django before. They quickly learned Django, but it is possible this fluency disparity may have caused an unintended bias in results–handicapping overall Django velocity.

sux0r 2.1.0 is a blogging package, an RSS aggregator, a bookmark repository, and a photo publishing platform with a focus on Naive Bayesian categorization and probabilistic content.

OpenID enabled (version 1.1); as both a consumer and a provider.

Srivastava realized that the same logic could be applied to the lottery. The apparent randomness of the scratch ticket was just a facade, a mathematical lie. And this meant that the lottery system might actually be solvable, just like those mining samples. “At the time, I had no intention of cracking the tickets,” he says. He was just curious about the algorithm that produced the numbers. Walking back from the gas station with the chips and coffee he’d bought with his winnings, he turned the problem over in his mind. By the time he reached the office, he was confident that he knew how the software might work, how it could precisely control the number of winners while still appearing random. “It wasn’t that hard,” Srivastava says. “I do the same kind of math all day long.”

Oxford mathematician Peter Donnelly reveals the common mistakes humans make in interpreting statistics -- and the devastating impact these errors can have on the outcome of criminal trials.