Data analysis: Statistical and computational methods for scientists and engineers, fourth edition

Abstract

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, • in working for bachelor or master degrees, • in thesis work, • in research and professional work.