Dec 22

Borel-Cantelli and Annihilation Events and more

As should be clear from the timestamps on previous posts, this blog is now mostly in hibernation mode. Meanwhile, I have been writing and recording podcast episodes, sometimes about topics related to what you used to find on this blog. If you want to continue to follow my thoughts on topics like how to evaluate the contents of black boxes, the proper understanding of tail risks,  and the use of humans as randomization devices, please subscribe to my substack and add my podcast to your favorite listening device.

Here’s a sampling of those articles and episodes:



• The Pleasures and Perils of Arbitrage (coming soon to my substack)

Betting Against Pascal

Black Box Thinking, UFOs, and a Fist Full of Dung

• Deborah Mayo on Error, Replication, and Severe Testing

• Scott Aaronson on the Hunt for Real Randomness

• Russ Roberts on the Curious Task of Epistemology

• Andrew Gelman on Data, Modeling, and Uncertainty Amidst the Forking Paths

• Cargo Cults


Feb 14

The week in stats (Feb. 24th edition)

Dec 13

The week in stats (Dec. 2nd edition)

Sep 13

The week in stats (Sept. 23th edition)

  • The Histomap of World History illustrates the rise and fall of various empires and civilizations through an increasing time series up to present day (because the original image is too large, we include a truncated version here in post). Did you know that you can create these visuals in R? Here is how to do them.
  • When we deal with time series modelling and forecasting, many people start with sophisticated models like the ARIMA or the GARCH. Rob Hyndman of Monash University suggests that when forecasting daily data, unless the the time series is very long, the eas­i­est approach is to sim­ply set the fre­quency attribute to 7. Then any of the usual time series fore­cast­ing meth­ods should pro­duce rea­son­able fore­casts.
  • Kaiser Fung, the owner of the popular statistics blog Junkcharts, interviews Andrew Gelman.
  • OpenStreetMap is crowdsourced map project.  Thousands of users log in each day, and help to improve the map by updating their neighborhood. Here is a visualization of this amazing social fabric of individuals working together. Every user is assigned different color, and their updates are represented on this map. Take a look at how many people have been mapping near you.
  • A series of four articles by Charlie Kufs of statswithcats on How to Write Data Analysis Reports.
  • What is the limiting distribution of a sum of weighted Gaussian?