Statistical Methods for Physical Science

by Elsevier Science

Overview

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

Product Details

ISBN-13:	9780080860169
Publisher:	Elsevier Science
Publication date:	12/13/1994
Sold by:	Barnes & Noble
Format:	eBook
Pages:	542
File size:	16 MB
Note:	This product may take a few minutes to download.

Table of Contents

W.R. Leo, Introduction to Probability Modeling. L. Hodges, Common Univariate Distributions. C. Chatfield, Random Process Models. N. Cressie, Models for Spatial Processes. P. Clifford, Monte Carlo Methods. J. Kitchin, Basic Statistical Inference. V.N. Nair and A.E. Freeny, Methods for Assessing Distributional Assumptions in One- and Two-Sample Problems. W.Q. Meeker and L.A. Escobar, Maximum Likelihood Methods for Fitting ParametricStatistical Models. G.A.F. Seber and C.J. Wild, Least Squares. W.J. Randel, Filtering and Data Preprocessing for Time Series Analysis. D.B. Percival, Spectral Analysis of Univariate and Bivariate Time Series. D.A. Lewis, Weak Periodic Signals in Point Process Data. D. Zimmerman, Statistical Analysis of Spatial Data. H.F. Martz and R.A. Waller, Bayesian Methods. J.M. Hauptman, Simulation of Physical Systems. J.L. Stanford and J.R. Ziemke, Field (Map) Statistics. F.L. Hulting and A.P. Jaworski, Modern Statistical Computing and Graphics. References. Tables. Subject Index.

Editorial Reviews

An introduction to probability and statistics for experimental physical scientists with a level of mathematical sophistication commensurate with graduate training in the physical sciences. Covers probability modeling, the basics of probability-based statistical inference including least squares analysis, statistical inference from time series and spatial data, and some specialized topics only applicable with the recent advances in scientific computing. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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