Jaynes, 2003 | Probability theory: the logic of science | comments

Going beyond the conventional mathematics of probability theory, this study views the subject in a wider context. It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.

The standard rules of probability can be interpreted as uniquely valid principles in logic. In this book, E. T. Jaynes dispels the imaginary distinction between 'probability theory' and 'statistical inference', leaving a logical unity and simplicity, which provides greater technical power and flexibility in applications. This book goes beyond the conventional mathematics of probability theory, viewing the subject in a wider context. New results are discussed, along with applications of probability theory to a wide variety of problems in physics, mathematics, economics, chemistry and biology. It contains many exercises and problems, and is suitable for use as a textbook on graduate level courses involving data analysis. The material is aimed at readers who are already familiar with applied mathematics at an advanced undergraduate level or higher. The book will be of interest to scientists working in any area where inference from incomplete information is necessary.

- Unique interpretation of probability theory, containing new and original work by the author
- Applications of probability theory to a wide range of problems in physics and other areas
- The interpretation of probability as an extension of logic, dispelling many of the paradoxes usually associated with probability theory

### Editorâ€™s foreword

# Preface

# I | Principles and elementary applications

# 1 | Plausible reasoning

# 2 | The quantitative rules

# 3 | Elementary sampling theory

# 4 | Elementary hypothesis testing

# 5 | Queer uses of probability theory

# 6 | Elementary parameter estimation

# 7 | The Central, Gaussian Or Normal Distribution