Scientific reasoning is—and ought to be—conducted in accordance with the axioms of probability. This Bayesian view—so called because of the central role it accords to a theorem first proved by Thomas Bayes in the late eighteenth ...

In clinical and agricultural trials, there is the danger that an experimental outcome appears to arise from the causal process or treatment one is interested in when, in reality, it was produced by some extraneous variation in the experimental conditions. The remedy prescribed by classical statisticians involves the procedure of randomization, whose effectiveness and appropriateness is criticized. An alternative, Bayesian analysis of experimental design, is shown, on the other hand, to provide a coherent and intuitively satisfactory solution to the problem.

Bacon's scientific method is commonly thought to proceed mechanically to its infallible end. In this book however, Urbach presents Bacon's philosophy in an alternative light which acquits him of several errors. Urbach describes Bacon as an experimental scientist and examines the criticisms made against him, one of which was that he did not understand the roles of mathematics and science. Bacon was not a traditional metaphysician and was alarmed at the lack of progress in science since ancient times, especially the (...) lack of practical results. He attempted to open up a middle path between practical experience and unsupported theorizing. The author intends to clarify rather than defend Bacon's work. (shrink)

Peter Urbach; X*—Random Sampling and the Principles of Estimation, Proceedings of the Aristotelian Society, Volume 89, Issue 1, 1 June 1989, Pages 143–164, http.

Mayo (1987) sought to discredit Urbach's (1985) arguments against randomization as a universal requirement in clinical and agricultural trials. The present reply rebuts Mayo's criticisms.

Peter Urbach; X*—Random Sampling and the Principles of Estimation, Proceedings of the Aristotelian Society, Volume 89, Issue 1, 1 June 1989, Pages 143–164, http.