When I describe priming studies to audiences, the reaction is often disbelief. This is not a surprise: System 2 believes that it is in charge and that it knows the reasons for its choices. Questions are probably cropping up in your mind as well: How is it possible for such trivial manipulations of the context to have such large effects? Do these experiments demonstrate that we are completely at the mercy of whatever primes the environment provides at any moment? Of course not. The effects of the primes are robust but not necessarily large. Among a hundred voters, only a few whose initial preferences were uncertain will vote differently about a school issue if their precinct is located in a school rather than in a church—but a few percent could tip an election.Little wonder he reacted so strongly, if counter-intuitive notions like this were foundational to his work and reputation.
The idea you should focus on, however, is that disbelief is not an option. The results are not made up, nor are they statistical flukes. You have no choice but to accept that the major conclusions of these studies are true. More important, you must accept that they are true about you. If you had been exposed to a screen saver of floating dollar bills, you too would likely have picked up fewer pencils to help a clumsy stranger. You do not believe that these results apply to you because they correspond to nothing in your subjective experience. But your subjective experience consists largely of the story that your System 2 tells itself about what is going on. Priming phenomena arise in System 1, and you have no conscious access to them.
In sharp contrast to this population genetic phenomenon of regression to the mean ... the term "regression to the mean" is now often used to describe completely different phenomena in which an initial sampling bias may disappear as new, repeated, or larger samples display sample means that are closer to the true underlying population mean.Don't feel bad, though. Lehrer made the same mistake in his article. [Others may describe this as just letting one phrase serve double duty. I choose to call it a mistake. Having spent time trying to explain and make clear a 100+ year old, very well understood statistical phenomenon to students, I resent someone lazily applying the same term to a completely different phenomenon.]
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posted by yoink at 10:35 AM on February 4 [4 favorites]