EBOOK
The Diagnostic Process
Graphic Approach to Probability and Inference in Clinical Medicine
Rudolf Zalter(0)
About
This book addresses the decision making process under uncertainty. The process commonly encountered in all fields of human endeavor is called the diagnostic process in this monograph.
The thrust of this book is to help the struggling student, of all ages, in all fields, to cross the threshold from rote to comprehension, thus bridging an intuitive gap left in many a readers mind regarding the significance and clinical implication of the accompanying probability data.
The text is, in essence, a verbal and graphic portrait of the basic ideas and symbolic structure of probability and statistical inference with particular stress on the Bayesian version. It aims to expound in words, simile, and diagrams the inherent connections obtained between a given event and its sample space or between a given random sample and a hypothesized population. In this sense, no formula is left naked to be absorbed on its face value without the support of a graphic cover. The final result is a firm grasp of the simple concepts that make the infrastructure (not the superstructure) of the subject.
Nonetheless, this is not another book on statistics. It certainly is not a textbook geared for the classroom, it contains no problem to solve other than those structured and graphed examples needed to clarify and illustrate the thrust of the point under consideration. The book deals exclusively with the two topics that I tend to believe are the core thesis of statistics, namely, probability and its counterpoint, inference, supported by the necessary exposition of sets. Thus, the book does not include the mandatory and important chapters on analysis of variance, regression, and correlation.
The thrust of this book is to help the struggling student, of all ages, in all fields, to cross the threshold from rote to comprehension, thus bridging an intuitive gap left in many a readers mind regarding the significance and clinical implication of the accompanying probability data.
The text is, in essence, a verbal and graphic portrait of the basic ideas and symbolic structure of probability and statistical inference with particular stress on the Bayesian version. It aims to expound in words, simile, and diagrams the inherent connections obtained between a given event and its sample space or between a given random sample and a hypothesized population. In this sense, no formula is left naked to be absorbed on its face value without the support of a graphic cover. The final result is a firm grasp of the simple concepts that make the infrastructure (not the superstructure) of the subject.
Nonetheless, this is not another book on statistics. It certainly is not a textbook geared for the classroom, it contains no problem to solve other than those structured and graphed examples needed to clarify and illustrate the thrust of the point under consideration. The book deals exclusively with the two topics that I tend to believe are the core thesis of statistics, namely, probability and its counterpoint, inference, supported by the necessary exposition of sets. Thus, the book does not include the mandatory and important chapters on analysis of variance, regression, and correlation.