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New publication asks if there is a Bayesian justification of hypothetico‐deductive inference

6 January 2021

A new publication from Professor Samir Okasha and Dr Karim Thebault asks if there is a Bayesian justification of hypothetico‐deductive inference, the proposed description of the scientific method.

The article has been published in the journal Nous.


Many philosophers have claimed that Bayesianism can provide a simple justification for hypothetico‐deductive (H‐D) inference, long regarded as a cornerstone of the scientific method. Following up a remark of van Fraassen (1985), we analyze a problem for the putative Bayesian justification of H‐D inference in the case where what we learn from observation is logically stronger than what our theory implies.

Firstly, we demonstrate that in such cases the simple Bayesian justification does not necessarily apply. Secondly, we identify a set of sufficient conditions for the mismatch in logical strength to be justifiably ignored as a “harmless idealization”. Thirdly, we argue, based upon scientific examples, that the pattern of H‐D inference of which there is a ready Bayesian justification is only rarely the pattern that one actually finds at work in science. Whatever the other virtues of Bayesianism, the idea that it yields a simple justification of a pervasive pattern of scientific inference appears to have been oversold.

Further information

Okasha S and Thebault K (2020). Is there a Bayesian justification of hypothetico‐deductive inference? Nous Volume 54, Issue 4 pp. 774-794.

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