Steven Pinker reviews Malcolm Gladwell's new book of old articles (all of which are available for free online), providing quite a good characterization of the strengths and weaknesses of Gladwell's writings more generally (pointer). Check out this quote (link added):
Gladwell frequently holds forth about statistics and psychology, and his lack of technical grounding in these subjects can be jarring. He provides misleading definitions of “homology,” “saggital plane” and “power law” and quotes an expert speaking about an “igon value” (that’s eigenvalue, a basic concept in linear algebra). In the spirit of Gladwell, who likes to give portentous names to his aperçus, I will call this the Igon Value Problem: when a writer’s education on a topic consists in interviewing an expert, he is apt to offer generalizations that are banal, obtuse or flat wrong.And he goes on to point out a flaw I find much more annoying:
The banalities come from a gimmick that can be called the Straw We. First Gladwell disarmingly includes himself and the reader in a dubious consensus — for example, that “we” believe that jailing an executive will end corporate malfeasance, or that geniuses are invariably self-made prodigies or that eliminating a risk can make a system 100 percent safe. He then knocks it down with an ambiguous observation, such as that “risks are not easily manageable, accidents are not easily preventable.”This technique is by no means exclusive to Gladwell. At least before I stopped reading it, this blog was almost all Straw We.
II
Earlier this year, I complained about Malcolm Gladwell's, um, creative use of the term "outliers". As my mind is in the habit of retaining the strangest of things, I recently remembered a comment from a blogpost of Gladwell's. The context is disagreement about car salesmen's strategies and Gladwell citing a particularly successful car salesman in support of his view. Which provoked the following comment:
No, they're not.
I submit that's where Gladwell got his book's title from.
When did sampling the 99th percentile of anything become a reliable sample? That's pretty shoddy fieldwork.
You gotta sample all the percentiles, or at least a reasonable range, to get quality data.
99th percentiles are usually known as "outliers."