Published online by Cambridge University Press: 01 April 2022
According to a standard account of evidence, one piece of information is stronger evidence for an hypothesis than is another iff the probability of the hypothesis on the one is greater than it is on the other. This condition, I argue, is neither necessary nor sufficient because various factors can strengthen the evidence for an hypothesis without increasing (and even decreasing) its probability. Contrary to what probabilists claim, I show that this obtains even if a probability function can take these evidential factors into account in ways they suggest and yield a unique probability value. Nor will the problem be solved by appealing to second-order probabilities.
For very helpful discussions and comments I am indebted to Laura J. Snyder. Robert Rynasiewicz and members of my 1992 NEH Summer Seminar for College Teachers, particularly Lee Brown, Henry Inman, Sam Mitchell, and J. D. Trout, offered useful criticisms. I am also grateful to two practitioners of probabilities at Johns Hopkins, Steven Goodman of the Department of Biostatistics, and Alan Goldman of the Department of Mathematical Sciences. Finally, I must thank Richard Jeffrey, my not-so-anonymous referee, for his sharp and witty barbs. Who can argue with a subjective Bayesian?