Synopses & Reviews
This book is a guide to the practical application of statistics to data analysis 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 then develop more advanced statistical ideas, focusing on interval estimation, characteristic functions, and correcting distributions for the effects of measurement errors (unfolding).
Review
"I believe the author did an admirable job in presenting a wealth of material in a limited space." -- W. Jason Owen, Technometrics, August 2000, Vol 42, No 3
Noted in Quarterly of Applied Mathematics, Vol LVIII, June 2000, No. 2
Review
"I believe the author did an admirable job in presenting a wealth of material in a limited space." -- W. Jason Owen, Technometrics, August 2000, Vol 42, No 3
Noted in Quarterly of Applied Mathematics, Vol LVIII, June 2000, No. 2
Synopsis
This book is a guide to the practical application of statistics to data analysis 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 then develop more advanced statistical ideas, focusing on interval estimation, characteristic functions, and correcting distributions for the effects of measurement errors (unfolding).
Table of Contents
Preface
Notation
1. Fundamental Concepts
2. Examples of Probability Functions
3. The Monte Carlo Method
4. Statistical Tests
5. General Concepts of Parameter Estimation
6. The Method of Maximum Likelihood
7. The Method of Least Squares
8. The Method of Moments
9. Statistical Errors, Confidence Intervals and Limits
10. Characteristic Functions and Related Examples
11. Unfolding
Bibliography
Index
Preface
Notation
1. Fundamental Concepts
2. Examples of Probability Functions
3. The Monte Carlo Method
4. Statistical Tests
5. General Concepts of Parameter Estimation
6. The Method of Maximum Likelihood
7. The Method of Least Squares
8. The Method of Moments
9. Statistical Errors, Confidence Intervals and Limits
10. Characteristic Functions and Related Examples
11. Unfolding
Bibliography
Index