Published research findings are sometimes refuted by subsequent evidence, says Ioannidis, with ensuing confusion and disappointment.

The Empire of Chance tells how quantitative ideas of chance transformed the natural and social sciences, as well as daily life over the last three centuries. A continuous narrative connects the earliest application of probability and statistics in gambling and insurance to the most recent forays into law, medicine, polling and baseball. Separate chapters explore the theoretical and methodological impact in biology, physics and psychology. Themes recur - determinism, inference, causality, free will, evidence, the shifting meaning of probability - but (...) in dramatically different disciplinary and historical contexts. In contrast to the literature on the mathematical development of probability and statistics, this book centres on how these technical innovations remade our conceptions of nature, mind and society. Written by an interdisciplinary team of historians and philosophers, this readable, lucid account keeps technical material to an absolute minimum. It is aimed not only at specialists in the history and philosophy of science, but also at the general reader and scholars in other disciplines. (shrink)

The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.

Dr Edwards' stimulating and provocative book advances the thesis that the appropriate axiomatic basis for inductive inference is not that of probability, with its addition axiom, but rather likelihood - the concept introduced by Fisher as a measure of relative support amongst different hypotheses. Starting from the simplest considerations and assuming no more than a modest acquaintance with probability theory, the author sets out to reconstruct nothing less than a consistent theory of statistical inference in science.

Because physical theories typically predict numerical values, an improvement in experimental precision reduces the tolerance range and hence increases corroborability. In most psychological research, improved power of a statistical design leads to a prior probability approaching 1/2 of finding a significant difference in the theoretically predicted direction. Hence the corroboration yielded by "success" is very weak, and becomes weaker with increased precision. "Statistical significance" plays a logical role in psychology precisely the reverse of its role in physics. This problem is (...) worsened by certain unhealthy tendencies prevalent among psychologists, such as a premium placed on experimental "cuteness" and a free reliance upon ad hoc explanations to avoid refutation. (shrink)

What Chow calls NHSTP is an inconsistent hybrid of Fisherian and Neyman-Pearsonian ideas. In psychology it has been practiced like ritualistic handwashing and sustained by wishful thinking about its utility. Chow argues that NHSTP is an important tool for ruling out chance as an explanation for data. I disagree. This ritual discourages theory development by providing researchers with no incentive to specify hypotheses.

The first of 3 objectives in this study was to address the major problem with Null Hypothesis Significance Testing (NHST) and 2 common misconceptions related to NHST that cause confusion for students and researchers. The misconcep- tions are (a) a smaller p indicates a stronger relationship and (b) statistical signifi- cance indicates practical importance. The second objective was to determine how this problem and the misconceptions were treated in 12 recent textbooks used in edu- cation research methods and statistics classes. (...) The third objective was to examine how the textbooks’ presentations relate to current best practices and how much help they provide for students. The results show that almost all of the textbooks fail to acknowledge that there is controversy surrounding NHST. Most of the textbooks dealt, at least minimally, with the alleged misconceptions of interest, but they pro- vided relatively little help for students. (shrink)