06 July 2011

Number One for 6 July 2011

  • This post is the most popular I've ever written, thanks to inadvertent SEO: Are tornadoes scary? [PMQT]
  • China is moving up the value chain. [Time]
  • More ideas on increasing classroom productivity in large-lecture situations. [The Chronicle]
  • Does absenteeism affect learning outcomes? Apparently by as much as a full letter grade. And larger and mathier courses mean more absenteeism. Consequently, this economist calls for strict regulation:
    A generation ago, both in principle and in practice, attendance at class was not optional. Today, often in principle and almost always i npractice, it is. Perhaps a return to the old system would make a large difference to learning. There is no way to find out but to try.
    [Journal of Economic Perspectives]
  • Of course, access to good teaching is like access to good healthcare: Money counts. [NYT]
  • Going on the bookshelf, someday:Berk on Regression:
    Presumes at least minimal familiarity with the math and practicalities of doing a multiple linear regression. The point of this book is to explain very clearly what regression can and cannot do, and especially to drive home the meaning and force of all the assumptions which are required to make the machinery of statistical inference for linear regression work. These assumptions are, or ought to be treated as, scientific hypotheses, which need to be not just taken for granted, or even listed mechanically and then ignored, but supported. (Many of them are hard to even assert with a straight face about important kinds of real data, never mind back up.) As he rightly says, the requirements for using regression for causal inference are even stronger, and the common practice of ignoring these issues, or hoping that they'll go away if you just use instrumental variables, has nothing to recommend it. (However, the discussion of Judea Pearl's work on causal inference in section 10.5 seems to me to be somewhat superficial, and even to misunderstand Pearl's book more than a little.) Of course, as descriptive summary of a data set, regression has much to recommend it; but not necessarily more than newer methods of data-mining, which he considers briefly in the conclusion.
    [Cosma Shalizi]

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