Improving Statistical Reasoning : Theoretical Models and Practical Implications

This book focuses on how statistical reasoning works and on training programs that can exploit people's natural cognitive capabilities to improve their statistical reasoning. Training programs that take into account findings from evolutionary psychology and instructional theory are shown to have substantially larger effects that are more stable over time than previous training regimens. The theoretical implications are traced in a neural network model of human performance on statistical reasoning problems. This book apppeals to judgment and decision making researchers and other cognitive scientists, as well as to teachers of statistics and probabilistic reasoning. Improving Statistical Reasoning presents new studies of how people think and act on probabilistic information, focusing on the details of how statistical reasoning works and on training programs that can exploit people's natural cognitive capabilities to improve their statistical reasoning. Training programs that take into account findings from evolutionary psychology and instructional theory are shown to have substantially larger effects that are more stable over time than previous training regimens. The theoretical implications of the work are presented in a neural network model of human performance on statistical reasoning problems. This book will be of interest to scholars in the fields of judgment and decision making and cognitive science, and to teachers of statistics and probabilistic reasoning. This book describes an approach to understanding, modeling, and improving the probabilistic reasoning of ordinary adults, comparing their reasoning to that of "experts." For specialists in judgment and decision making and all cognitive scientists.