COVID-19 Update: We are currently shipping orders daily. However, due to transit disruptions in some geographies, deliveries may be delayed. To provide all customers with timely access to content, we are offering 50% off Science and Technology Print & eBook bundle options. Terms & conditions.
Statistical Methods for Physical Science - 1st Edition - ISBN: 9780124759732, 9780080860169

Statistical Methods for Physical Science

1st Edition

0.0 star rating Write a review
Serial Volume Editors: John Stanford Stephen Vardeman
Hardcover ISBN: 9780124759732
eBook ISBN: 9780080860169
Imprint: Academic Press
Published Date: 8th November 1994
Page Count: 542
Sales tax will be calculated at check-out Price includes VAT/GST
Price includes VAT/GST

Institutional Subscription

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.


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.

Key Features

  • 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


Graduate students and researchers in physics, geophysics, materials science, chemistry, optics; and applied statisticians with clients in these fields

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.


No. of pages:
© Academic Press 1994
8th November 1994
Academic Press
Hardcover ISBN:
eBook ISBN:

About the Serial Volume Editors

John Stanford

Affiliations and Expertise

Iowa State University

Stephen Vardeman

Affiliations and Expertise

Iowa State University

Ratings and Reviews