Statistical Data Analysis by Glen CowanStatistical Data Analysis by Glen Cowan

Statistical Data Analysis

byGlen Cowan

Paperback | March 1, 1998

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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 takenfrom 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).

About The Author

Dr Glen D. Cowan, CERN, PPE Division, CH-1211 Geneva 23, Switzerland, Tel: +41 22 767 6539, Fax: +41 22 767 9425, Email: Glen Cowan received his Ph.D. in physics in 1988 from the University of California, Berkeley, after completing his thesis work on particle production in high energy electron-positron collisions. Fr...

Details & Specs

Title:Statistical Data AnalysisFormat:PaperbackDimensions:212 pages, 9.21 × 6.14 × 0.47 inPublished:March 1, 1998Publisher:Oxford University Press

The following ISBNs are associated with this title:

ISBN - 10:0198501552

ISBN - 13:9780198501558

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Table of Contents

PrefaceNotation1. Fundamental Concepts2. Examples of Probability Functions3. The Monte Carlo Method4. Statistical Tests5. General Concepts of Parameter Estimation6. The Method of Maximum Likelihood7. The Method of Least Squares8. The Method of Moments9. Statistical Errors, Confidence Intervals and Limits10. Characteristic Functions and Related Examples11. UnfoldingBibliographyIndex

Editorial Reviews

"The material presented in this book is dense.In less than two hundred pages, it takes the reader from the basic notions of probability, through neural networks, Monte Carlo methods, and regularization techniques." Short Book Reviews