Statistical Data Analysis
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Product details:
- Publisher OUP Oxford
- Date of Publication 26 March 1998
- ISBN 9780198501558
- Binding Paperback
- No. of pages212 pages
- Size 235x156x12 mm
- Weight 317 g
- Language English
- Illustrations line figures, tables 0
Categories
Short description:
The book is a guide to the practical application of statistics in data analysis as typically encountered in the physical sciences. It is primarily addressed at students and researchers who work with experimental data. The topics include probability, random variables, Monte Carlo techniques, statistical tests, parameter estimation, and unfolding methods.
MoreLong description:
This book is a guide to the practical application of statistics in data analysis as typically encountered in the physical sciences. It is primarily addressed at students and professionals who need to draw quantitative conclusions from experimental data. Although most of the examples are taken from particle physics, the material is presented in a sufficiently general way as to be useful to people from most branches of the physical sciences. The first part of the book describes the basic tools of data analysis: concepts of probability and random variables, Monte Carlo techniques, statistical tests, and methods of parameter estimation. The last three chapters are somewhat more specialized than those preceding, covering interval estimation, characteristic functions, and the problem of correcting distributions for the effects of measurement errors (unfolding).
"Glen Cowan is a particle physicist who seems to have got everything right. Results are stated clearly, without mathematical proof but with enough explanation to satisfy the physicist's need to understand not only how, but also why...Those teaching an advanced undergraduate or graduate course in statistics or physicists will find this a good textbook...Do not be fooled by the fact that it does not have the "textbook look" - the exercises have been made available separately on a Web site. " CERN Courier
Table of Contents:
Preface
Notation
Fundamental Concepts
Examples of Probability Functions
The Monte Carlo Method
Statistical Tests
General Concepts of Parameter Estimation
The Method of Maximum Likelihood
The Method of Least Squares
The Method of Moments
Statistical Errors, Confidence Intervals and Limits
Characteristic Functions and Related Examples
Unfolding
Bibliography
Index
