Popper's falsification and corroboration from the statistical perspectives
Youngjo Lee, Yudi Pawitan

TL;DR
This paper explores Popper's philosophical views on falsification and corroboration from a statistical perspective, emphasizing the importance of likelihood as a non-probabilistic measure of evidence.
Contribution
It introduces the likelihood concept to non-statistical audiences, highlighting its alignment with Popperian falsification and its potential to clarify debates on hypothesis testing.
Findings
Likelihood is a non-probabilistic measure of corroboration.
Likelihood aligns with Popperian falsification principles.
Historical development of likelihood spans over 100 years.
Abstract
The role of probability appears unchallenged as the key measure of uncertainty, used among other things for practical induction in the empirical sciences. Yet, Popper was emphatic in his rejection of inductive probability and of the logical probability of hypotheses; furthermore, for him, the degree of corroboration cannot be a probability. Instead he proposed a deductive method of testing. In many ways this dialectic tension has many parallels in statistics, with the Bayesians on logico-inductive side vs the non-Bayesians or the frequentists on the other side. Simplistically Popper seems to be on the frequentist side, but recent synthesis on the non-Bayesian side might direct the Popperian views to a more nuanced destination. Logical probability seems perfectly suited to measure partial evidence or support, so what can we use if we are to reject it? For the past 100 years,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
