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Archive of posts filed under the Miscellaneous Statistics category.

Skepticism about a published claim regarding income inequality and happiness

Frank de Libero writes: I read your Chance article (disproving that no one reads Chance!) re communicating about flawed psychological research. And I know from your other writings of your continuing good fight against misleading quantitative work. I think you and your students might be interested on my recent critique of a 2011 paper published […]

Ethics and statistics

I spoke (remotely) recently at the University of Wisconsin, on the topic of ethics and statistics. Afterward, I received the following question from Fabrizzio Sanchez: As hard as it is to do, I thought it was good to try and define what exactly makes for an ethical violation. Your third point noted that it needed […]

Stan World Cup update

The other day I fit a simple model to estimate team abilities from World Cup outcomes. I fit the model to the signed square roots of the score differentials, using the square root on the theory that when the game is less close, it becomes more variable. 0. Background As you might recall, the estimated […]

D&D 5e: Probabilities for Advantage and Disadvantage

The new rules for D&D 5e (formerly known as D&D Next) are finally here: Dungeons & Dragons, 5th Edition: Basic Rules D&D 5e introduces a new game mechanic, advantage and disadvantage. Basic d20 Rules Usually, players roll a 20-sided die (d20) to resolve everyting from attempts at diplomacy to hitting someone with a sword. Each […]

Open-source tools for running online field experiments

Dean Eckles points me to this cool new tool for experimentation: I [Eckles] just wanted to share that in a collaboration between Facebook and Stanford, we have a new paper out about running online field experiments. One thing this paper does is describe some of the tools we use to design, deploy, and analyze experiments, […]

Visualizing sampling error and dynamic graphics

Robert Grant writes: What do you think of this visualisation from the NYT [in an article by Neil Irwin and Kevin Quealy but I'm not sure if they're the designers of the visualization]? I’m pretty impressed as a method of showing sampling error to a general audience! I agree. P.S. In related news, Antony Unwin […]

Dimensionless analysis as applied to swimming!

We have no fireworks-related posts for July 4th but at least we have an item that’s appropriate for the summer weather. It comes from Daniel Lakeland, who writes: Recently in one of your blog posts (“priors I don’t believe”) there was a discussion in which I was advocating the use of dimensional analysis and dimensionless […]

“The great advantage of the model-based over the ad hoc approach, it seems to me, is that at any given time we know what we are doing.”

The quote is from George Box, 1979. And this: Please can Data Analysts get themselves together again and become whole Statisticians before it is too late? Before they, their employers, and their clients forget the other equally important parts of the job statisticians should be doing, such as designing investigations and building models? I actually […]

DataKind Opportunity Analyst Job Opening

Jake Porway writes: DataKind is looking for a brilliant part-time Opportunity Analyst to find data-informed solutions to the world’s most pressing problems with our NYC team! We’re a fast growing non-profit that tackles humanity’s biggest problems through data science. . . . We’ve helped the World Bank estimate poverty from satellite imagery, teamed with the […]

As if we needed another example of lying with statistics and not issuing a correction: bike-share injuries

This post is by Phil Price A Washington Post article says “In the first study of its kind, researchers from Washington State University and elsewhere found  a 14 percent greater risk of head injuries to cyclists associated with cities that have bike share programs. In fact, when they compared raw head injury data for cyclists […]