Revisiting Popper’s Demarcation of Science 2017

28 July 1902- 17 Sept. 1994

Karl Popper died on September 17 1994. One thing that gets revived in my new book (Statistical Inference as Severe Testing, 2018, CUP) is a Popperian demarcation of science vs pseudoscience Here’s a snippet from what I call a “live exhibit” (where the reader experiments with a subject) toward the end of a chapter on Popper:

Live Exhibit. Revisiting Popper’s Demarcation of Science: Here’s an experiment: Try shifting what Popper says about theories to a related claim about inquiries to find something out. To see what I have in mind, join me in watching a skit over the lunch break:

Physicist: “If mere logical falsifiability suffices for a theory to be scientific, then, we can’t properly oust astrology from the scientific pantheon. Plenty of nutty theories have been falsified, so by definition they’re scientific. Moreover, scientists aren’t always looking to subject well corroborated theories to “grave risk” of falsification.”

Fellow traveler: “I’ve been thinking about this. On your first point, Popper confuses things by making it sound as if he’s asking: When is a theory unscientific? What he is actually asking or should be asking is: When is an inquiry into a theory, or an appraisal of claim H unscientific? We want to distinguish meritorious modes of inquiry from those that are BENT. If the test methods enable ad hoc maneuvering, sneaky face-saving devices, then the inquiry–the handling and use of data–is unscientific. Despite being logically falsifiable, theories can be rendered immune from falsification by means of cavalier methods for their testing. Adhering to a falsified theory no matter what is poor science. On the other hand, some areas have so much noise that you can’t pinpoint what’s to blame for failed predictions. This is another way that inquiries become bad science.”

She continues: Continue reading

Categories: Error Statistics, Popper, pseudoscience, science vs pseudoscience | Tags: | 10 Comments

A new front in the statistics wars? Peaceful negotiation in the face of so-called ‘methodological terrorism’

images-30I haven’t been blogging that much lately, as I’m tethered to the task of finishing revisions on a book (on the philosophy of statistical inference!) But I noticed two interesting blogposts, one by Jeff Leek, another by Andrew Gelman, and even a related petition on Twitter, reflecting a newish front in the statistics wars: When it comes to improving scientific integrity, do we need more carrots or more sticks? 

Leek’s post, from yesterday, called “Statistical Vitriol” (29 Sep 2016), calls for de-escalation of the consequences of statistical mistakes:

Over the last few months there has been a lot of vitriol around statistical ideas. First there were data parasites and then there were methodological terrorists. These epithets came from established scientists who have relatively little statistical training. There was the predictable backlash to these folks from their counterparties, typically statisticians or statistically trained folks who care about open source.
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Categories: Anil Potti, fraud, Gelman, pseudoscience, Statistics | 15 Comments

P-value madness: A puzzle about the latest test ban (or ‘don’t ask, don’t tell’)



Given the excited whispers about the upcoming meeting of the American Statistical Association Committee on P-Values and Statistical Significance, it’s an apt time to reblog my post on the “Don’t Ask Don’t Tell” policy that began the latest brouhaha!

A large number of people have sent me articles on the “test ban” of statistical hypotheses tests and confidence intervals at a journal called Basic and Applied Social Psychology (BASP)[i]. Enough. One person suggested that since it came so close to my recent satirical Task force post, that I either had advance knowledge or some kind of ESP. Oh please, no ESP required.None of this is the slightest bit surprising, and I’ve seen it before; I simply didn’t find it worth blogging about (but Saturday night is a perfect time to read/reread the (satirical) Task force post [ia]). Statistical tests are being banned, say the editors, because they purport to give probabilities of null hypotheses (really?) and do not, hence they are “invalid”.[ii] (Confidence intervals are thrown in the waste bin as well—also claimed “invalid”).“The state of the art remains uncertain” regarding inferential statistical procedures, say the editors.  I don’t know, maybe some good will come of all this.

Yet there’s a part of their proposal that brings up some interesting logical puzzles, and logical puzzles are my thing. In fact, I think there is a mistake the editors should remedy, lest authors be led into disingenuous stances, and strange tangles ensue. I refer to their rule that authors be allowed to submit papers whose conclusions are based on allegedly invalid methods so long as, once accepted, they remove any vestiges of them! Continue reading

Categories: P-values, pseudoscience, reforming the reformers, Statistics | 7 Comments

Popper on pseudoscience: a comment on Pigliucci (i), (ii) 9/18, (iii) 9/20



Jump to Part (ii) 9/18/15 and (iii) 9/20/15 updates

I heard a podcast the other day in which the philosopher of science, Massimo Pigliucci, claimed that Popper’s demarcation of science fails because it permits pseudosciences like astrology to count as scientific! Now Popper requires supplementing in many ways, but we can get far more mileage out of Popper’s demarcation than Pigliucci supposes.

Pigliucci has it that, according to Popper, mere logical falsifiability suffices for a theory to be scientific, and this prevents Popper from properly ousting astrology from the scientific pantheon. Not so. In fact, Popper’s central goal is to call our attention to theories that, despite being logically falsifiable, are rendered immune from falsification by means of ad hoc maneuvering, sneaky face-saving devices, “monster-barring” or “conventionalist stratagems”. Lacking space on Twitter (where the “Philosophy Bites” podcast was linked), I’m placing some quick comments here. (For other posts on Popper, please search this blog.) Excerpts from the classic two pages in Conjectures and Refutations (1962, pp. 36-7) will serve our purpose:

It is easy to obtain confirmations, or verifications, for nearly every theory–if we look for confirmations.



Confirmations should count only if they are the result of risky predictions; that is [if the theory or claim H is false] we should have expected an event which was incompatible with the theory [or claim]….

Every genuine test of a theory is an attempt to falsify it, or to refute it. Testability is falsifiability, but there are degrees of testability, some theories are more testable..

Confirming evidence should not count except when it is the result of a genuine test of the theory, and this means that it can be presented as a serious but unsuccessful attempt to falsify the theory. (I now speak of such cases as ‘corroborating evidence’).

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Categories: Error Statistics, Popper, pseudoscience, Statistics | Tags: , | 5 Comments

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