Trials and Errors. Jonah Lehrer's latest piece in Wired is a sort of sequel to his earlier article in the New Yorker on the decline effect (previously). Where that article focused on the institutional factors interfering with the accumulation of truth, this one focuses on the philosophical issues of causation and correlation in modern science. [Via]
posted by homunculus on Jan 5, 2012 - 22 comments

Correlation or Causation? Statistics are easy: All you need are two graphs and a leading question.
posted by beaucoupkevin on Dec 13, 2011 - 29 comments

Everyone knows that correlation doesn't imply causation, but researchers invariably need to come up with plausible explanations (i.e., models) for the patterns found in their data. However, very different models can "explain" the same pattern. The books The Bottom Billion: Why the Poorest Countries are Failing and What Can Be Done About It and Wars, Guns and Votes: Democracy in Dangerous Places by Oxford economist Paul Collier try to explain why some countries have remained poor using data from econometric studies. In his very interesting review (PDF), Mike McGovern, a political anthropologist at Yale, critiques the types of explanations found in popular economics books. Statistician Andrew Gelman has further thoughts on descriptive statistics, causal inference, and story time.
posted by Jasper Friendly Bear on Jul 13, 2011 - 59 comments

BBC News is running a weekly ongoing series of articles that describe and illustrate common misconceptions (and manipulations) of statistics using examples from the news and ads.
Lesson 1: surveys. Lesson 2: counting. Lesson 3: percentage. Lesson 4: averages. Lesson 5: causation.
posted by Tehanu on Sep 3, 2008 - 46 comments