Publisher Description

This well-respected introduction to statistics and statistical theory covers data processing, probability and random variables, utility and descriptive statistics, computation of Bayes strategies, models, testing hypotheses and much more. Clearly written, brief, well-indexed and abundantly equipped with exercise material.

Author Biography

Herman Chernoff is Professor Emeritus of Applied Mathematics at MIT and of Statistics at Harvard University. His research has focused on sample theory, optimal design of experiments, sequential analysis, and sequential design of experiments.Lincoln E. Moses (1921-2006), was Professor Emeritus of Health Research and Policy and of Statistics at Stanford University, where he spearheaded the development of biostatistics.

Table of Contents

1 INTRODUCTION 2 DATA PROCESSING 3 INTRODUCTION TO PROBABILITY AND RANDOM VARIABLES 4 UTILITY AND DESCRIPITIVE STATISTICS 5 UNCERTAINTY DUE TO IGNORANCE OF THE STATE OF NATURE 6 THE COMPUTATION OF BAYES STRATEGIES 7 INTRODUCTION TO CLASSICAL STATISTICS 8 MODELS 9 TESTING HYPOTHESES 10 ESTIMATION AND CONFIDENCE INTERVALS APPENDIX A NOTATION B MATHEMATICAL TABLES C TABLES OF RANDOM DEVIATES D TABLES OF PROBABILITY DISTRIBUTIONS E DERIVATIONS F MISCELLANEOUS REMARKS ABOUT GAME THEORY AND UTILITY THEORY PARTIAL LIST OF ANSWERS TO EXERCISES INDEX

Long Description

Beginners will find this well-respected introduction to statistics and statistical theory a motivating introduction to important mathematical notions such as set, function, and convexity. Other topics include data processing, probability, and random variables, models, testing hypotheses, and much more. Clearly written, brief, well-indexed, and abundantly equipped with exercise material. 1959 edition.

Details