TY  - BOOK
AU  - E.T. Jaynes
TI  - Probability theory : : the logic of science
SN  - 9780521592710
AV  - QA273 
PY  - 2003///]
CY  - U.K.
PB  - Cambridge University Press
KW  - Mathematics
N1  - Part I - Principles and elementary applications 
1 - Plausible reasoning 
2 - The quantitative rules 
3 - Elementary sampling theory
4 - Elementary hypothesis testing 
5 - Queer uses for probability theory 
6 - Elementary parameter estimation 
7 - The central, Gaussian or normal distribution 
8 - Sufficiency, ancillarity, and all that 
9 - Repetitive experiments: probability and frequency 
10 - Physics of ‘random experiments’ 

Part II - Advanced applications 
11 - Discrete prior probabilities: the entropy principle 
12 - Ignorance priors and transformation groups 
13 - Decision theory, historical background 
14 - Simple applications of decision theory 
15 - Paradoxes of probability theory 
16 - Orthodox methods: historical background 
17 - Principles and pathology of orthodox statistics 
18 - The Ap distribution and rule of succession 
19 - Physical measurements 
20 - Model comparison 
21 - Outliers and robustness 
22 - Introduction to communication theory
N2  - 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. --- summary provided by publisher
ER  -