LOGICIST STATISTICS I - MODELS AND MODELING

Arguments are presented to support increased emphasis on logical aspec ts of formal methods of analysis, depending on probability in the sens e of R. A. Fisher. Formulating probabilistic models that convey uncert ain knowledge of objective phenomena and using such models for inducti ve reasoning are central activities of individuals that introduce limi ted but necessary subjectivity into science. Statistical models are cl assified into overlapping types called here empirical, stochastic and predictive, all drawing on a common mathematical theory of probability , and all facilitating statements with logical and epistemic content. Contexts in which these ideas are intended to apply are discussed via three major examples.