Shogenji’s new measure of Bayesian justification

April 6, 2010

Proponents of Bayesian epistemology have invented several different quantitative measures of how available evidence bears on different hypotheses. These measures are referred to as measures of evidential support, coherence, confirmation, or justification, depending a bit on the precise significance ascribed to them. Presently, Bayesians disagree over which of these measure is the most useful, but a new paper by Shogenji provides very appealing alternative measure and, with some luck, may even settle this debate.

At first sight, it might appear that the posterior probability P(h|e) of a hypothesis h conditional on observed evidence e is the perfect measure for a Bayesian. However, a hypothesis sometimes has a high posterior probability simply by virtue of a high prior probability, without necessarily being support/confirmed/justified by virtue of the observed evidence. Read the rest of this entry »


More thoughts about the work of Dembski and Marks

January 4, 2010

More thoughts about Dembski and Marks’ project:

Is information, or constraints on inference, all there is?

July 26, 2009

“What is information? Is it physical? We argue that in a Bayesian theory the notion of information must be defined in terms of its effects on the beliefs of rational agents. Information is whatever constrains rational beliefs and therefore it is the force that induces us to change our minds.” — Ariel Caticha (eprint: 0710.1068)

“Perhaps physics is nothing but inference after all.” — Ariel Caticha (eprint: 0808.1260)

“Physics is the ability to win a bet.” — Attributed to J. R. Buck by C. A. Fuchs (eprint: quant-ph/0105039, p. 125)

Some theories present us with intruiging conceptual puzzles. This is the case with probability theory and statistics. Originally the notion of ‘probability’ was introduced in the study of games of chance, where players who are uncertain about outcomes in a game need to decide on a strategy. Read the rest of this entry »