Centre de documentation
scientifique

Data Analysis / Siegmund Brandt (2014)  

Public Titre : Data Analysis : Statistical and Computational Methods for Scientists and Engineers Type de document : Monographie Auteurs : Siegmund Brandt, Auteur Editeur : Springer International Publishing Année de publication : 2014 Importance : 532 p. ISBN/ISSN/EAN : 978-3-319-03762-2 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques [Termes IGN] analyse de variance [Termes IGN] méthode de Monte-Carlo [Termes IGN] méthode des moindres carrés [Termes IGN] méthode du maximum de vraisemblance (estimation) [Termes IGN] probabilités [Termes IGN] régression [Termes IGN] série temporelle [Termes IGN] statistiques [Termes IGN] variable aléatoire Résumé : (éditeur) 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. Note de contenu : 1- Introduction 2- Probabilities 3- Random Variables: Distributions 4- Computer Generated Random Numbers: The Monte Carlo Method 5- Some Important Distributions and Theorems 6- Samples 7- The Method of Maximum Likelihood 8- Testing Statistical Hypotheses 9- The Method of Least Squares 10- Function Minimization 11- Analysis of Variance 12- Linear and Polynomial Regression 13- Time Series Analysis Numéro de notice : 25778 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE Nature : Monographie En ligne : https://doi.org/10.1007/978-3-319-03762-2 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94973