Statistical Methods for Physical Science

Author: Stanford   John L.;Vardeman   Stephen B.  

Publisher: Elsevier Science‎

Publication year: 1994

E-ISBN: 9780080860169

P-ISBN(Paperback): 9780124759732

P-ISBN(Hardback):  9780124759732

Subject: O414.2 statistical physics

Language: ENG

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Description

This volume of Methods of Experimental Physics provides an extensive introduction to probability and statistics in many areas of the physical sciences, with an emphasis on the emerging area of spatial statistics. The scope of topics covered is wide-ranging-the text discusses a variety of the most commonly used classical methods and addresses newer methods that are applicable or potentially important. The chapter authors motivate readers with their insightful discussions.

  • Examines basic probability, including coverage of standard distributions, time series models, and Monte Carlo methods
  • Describes statistical methods, including basic inference, goodness of fit, maximum likelihood, and least squares
  • Addresses time series analysis, including filtering and spectral analysis
  • Includes simulations of physical experiments
  • Features applications of statistics to atmospheric physics and radio astronomy
  • Covers the increasingly important area of modern statistical computing

Chapter

Front Cover

pp.:  1 – 4

Copyright Page

pp.:  5 – 6

Contents

pp.:  6 – 14

Contributors

pp.:  14 – 16

Preface

pp.:  16 – 22

Chapter 2. Common Univariate Distributions

pp.:  56 – 84

Chapter 3. Random Process Models

pp.:  84 – 114

Chapter 4. Models for Spatial Processes

pp.:  114 – 146

Chapter 5. Monte Carlo Methods

pp.:  146 – 176

Chapter 6. Basic Statistical Inference

pp.:  176 – 208

Chapter 7. Methods for Assessing Distributional Assumptions in One- and Two-Sample Problems

pp.:  208 – 232

Chapter 8. Maximum Likelihood Methods for Fitting Parametric Statistical Models

pp.:  232 – 266

Chapter 9: Least Squares

pp.:  266 – 304

Chapter 10. Filtering and Data Preprocessing for Time Series Analysis

pp.:  304 – 334

Chapter 11. Spectral Analysis of Univariate and Bivariate Time Series

pp.:  334 – 370

Chapter 12. Weak Periodic Signals in Point Process Data

pp.:  370 – 396

Chapter 13. Statistical Analysis of Spatial Data

pp.:  396 – 424

Chapter 14. Bayesian Methods

pp.:  424 – 454

Chapter 15. Simulation of Physical Systems

pp.:  454 – 478

Chapter 16. Field (Map) Statistics

pp.:  478 – 502

Chapter 17. Modern Statistical Computing and Graphics

pp.:  502 – 542

Tables

pp.:  542 – 552

Index

pp.:  552 – 564

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