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Tag Archives: statistical analysis
Dead salmon finds home. Still dead.
It isn’t breaking news, and it’s hardly science. Still, considering last month’s discussion of statistical rigor and the recent kerfuffle over a paper in a well-respected psychological journal purporting extra sensory perception, now is the perfect time to revisit the dead salmon study.
In 2005, a graduate student in the lab of Abigail Baird at Dartmouth College needed to test his fMRI protocols for an upcoming experiment. Having already tested a pumpkin and a cornish game hen, the obvious next step was to scan a whole salmon from the local supermarket.
Why empiricism will always be imperfect
A new year is upon us, and that’s always a great time to clean out the skeletons in your closet. So without further ado, let’s take a look at Jonah Lehrer’s explanation of “the decline effect” (published in The New Yorker last month). Lehrer describes this odd phenomenon whereby statistical significance of previous scientific findings seems to decrease with age, as we get further and further away from the time that it was initially reported in literature.
As any scientist can tell you, the holy grail of an experiment is a low p-value, a statistical measure that tells whether your findings are indicative of an actual effect, not just randomness and chance. This sounds fairly straightforward – of course we want to find things of actual importance, rather than being lulled into a false discovery by arbitrary data – but it turns out to be much hazier than a simple “yes” or “no.”