Popper's Falsification and Corroboration from the Statistical Perspectives
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 the logicoinductive side vs. the nonBayesians or the frequentists on the other side. Simplistically Popper seems to be on the frequentist side, but recent synthesis on the nonBayesian 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, statisticians have developed a related concept called likelihood. As a measure of corroboration, the likelihood satisfies the Popperian requirement that it is not a probability. Our aim is to introduce the likelihood and its recent extension via a discussion of two wellknown logical fallacies in order to highlight that its lack of recognition may have led to unnecessary confusion in our discourse about falsification and corroboration of hypotheses.
 Publication:

3rd Karl Popper's Science and Philosophy
 Pub Date:
 2021
 DOI:
 10.1007/9783030670368_7
 arXiv:
 arXiv:2007.00238
 Bibcode:
 2021kpsp.book..121L
 Keywords:

 Statistics  Other Statistics
 EPrint:
 doi:10.1007/9783030670368_7