Data Analysis - Statistical and Computational Methods for Scientists and Engineers (Paperback, Softcover reprint of the original 3rd ed. 1999)

Bridging the gap between statistical theory and physical experiment, this is a thorough introduction to the statistical methods used in the experimental physical sciences and to the numerical methods used to implement them. The treatment emphasises concise but rigorous mathematics but always retains its focus on applications. Readers are assumed to have a sound basic knowledge of differential and integral calculus and some knowledge of vectors and matrices. After an introduction to probability, random variables, computer generation of random numbers and important distributions, the book turns to statistical samples, the maximum likelihood method, and the testing of statistical hypotheses. The discussion concludes with several important statistical methods: least squares, analysis of variance, polynomial regression, and analysis of time series. Appendices provide the necessary methods of matrix algebra, combinatorics, and many sets of useful algorithms and formulae.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Release date:	October 2012
First published:	1999
Translators:	Glen Gowan
Authors:	Siegmund Brandt
Dimensions:	235 x 155 x 35mm (L x W x T)
Format:	Paperback
Pages:	652
Edition:	Softcover reprint of the original 3rd ed. 1999
ISBN-13:	978-1-4612-7147-5
Categories:	Books > Reference & Interdisciplinary > Interdisciplinary studies > General Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Physics > General Books > Science & Mathematics > Mathematics > Applied mathematics > General
LSN:	1-4612-7147-9
Barcode:	9781461271475

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