Data Analysis: Statistical and Computational Methods for Scientists and Engineers

by Siegmund Brandt

Introduction The fourth edition of this successful textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Equal weight is given to statistical theory and practical problems. The concise mathematical treatment of the subject matter is illustrated by many examples, and for the present edition a library of Java programs has been developed. It comprises methods of numerical data analysis and graphical representation as well as many example programs and solutions to programming problems. The programs (source code, Java classes, and documentation) and extensive appendices to the main text are available for free download from the book’s page at www.springer.com. Contents Probabilities. Random variables. Random numbers and the Monte Carlo Method. Statistical distributions (binomial, Gauss, Poisson). Samples. Statistical tests. Maximum Likelihood. Least Squares. Regression. Minimization. Analysis of Variance. Time series analysis. Audience The book is conceived both as an introduction and as a work of reference. In particular it addresses itself to students, scientists and practitioners in science and engineering as a help in the analysis of their data in laboratory courses, working for bachelor or master degrees, in thesis work, and in research and professional work. “The book is concise, but gives a sufficiently rigorous mathematical treatment of practical statistical methods for data analysis; it can be of great use to all who are involved with data analysis.” Physicalia “This lively and erudite treatise covers the theory of the main statistical tools and their practical applications…a first rate university textbook, and good background material for the practicing physicist.” Physics Bulletin

774 pages, Kindle Edition

First published November 25, 1998

Reviews

[Amr Khaled · Rating 1 out of 5]

Right off the bat, it was very obvious that this book required a heavy backbone of statistics, one that I unfortunately do not have.
I stuck with it in the hopes that it might enlighten me about those weaknesses of knowledge that I have, alas that did not happen.
By the end, the book kept rambling about equations which I only saw in them the demise of my dreams to understand them.
My hope is for another book to salvage me.