Skip to Content


In case you missed them, here are some articles from September of particular interest to R users:

Todd Schneider wrote an algorithm in R to find the "most concave" US state (it's NY), and created an animation to show how it works.

We're thrilled to have John Wallace and Tess Nesbitt from DataSong join our Fall webinar series tomorrow, with a great presentation on time to event models.

Tableau, the popular interactive data visualization tool, is coming out with a new 8.1 update, and it will include integration with the R language.

As just about every statistics student can attest, Simpson's Paradox — a statistical phenomenon where an apparent trend is reversed when you look at subgroups — is notoriously hard to explain. You can look at examples — say, the fact that US wages are rising overall, but dropping within every educational group — but that don't really help to explain the paradox. 

As one of those people who always watches attentively before takeoff, I appreciate it when airlines take the time to make a good airline safety video. (Thank you, Virgin America, Delta, and Air New Zealand.) This one isn't real, it sure is funny (via Andrew Sullivan):


Have a great weekend -- we'll be back on Monday.

At the Journey to ROI event hosted by Accenture Analytics in San Francisco last week, four analytics executives held a panel discussion on how organizations can derive ROI from their analytics operations. On the panel was:

  • Brian McCarthy, Managing Director, Innovation, Accenture Analytics
  • Kevin Leighton, VP Partner Transformation Operations, HP
  • Simon Arkell, CEO Predixion Software
  • Dave Rich, CEO Revolution Analytics

You can watch the recording of the discussion below:


If you haven't already registered, don't miss tomorrow's webinar presented by Cloudera's Director of Product Strategy, Jairam Ranganathan and Michele Chambers, Chief Strategy Officer at Revolution Analytics.

If you missed last week's webinar with John Kreisa from Hortonworks (hosted by Data Science Central), we described how R fits into the Modern Data Architecture.