Introductory Statistics with R

2. Auflage 2008
ISBN: 978-0-387-79053-4
Verlag: Springer-Verlag GmbH

Buch, Englisch, 364 Seiten, Format (B × H): 156 mm x 236 mm, Gewicht: 1190 g

Reihe: Statistics and Computing

This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. 

All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one- and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Dalgaard, Peter

Fachgebiete

• Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
• Mathematik | Informatik EDV | Informatik Informatik
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
• Naturwissenschaften Biowissenschaften Biowissenschaften
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung

Inhaltsverzeichnis

Basics.- The R environment.- Probability and distributions.- Descriptive statistics and graphics.- One- and two-sample tests.- Regression and correlation.- Analysis of variance and the Kruskal–Wallis test.- Tabular data.- Power and the computation of sample size.- Advanced data handling.- Multiple regression.- Linear models.- Logistic regression.- Survival analysis.- Rates and Poisson regression.- Nonlinear curve fitting.

Über Autor(innen)

Peter Dalgaard is associate professor at the Biostatistical Department at the University of Copenhagen and has extensive experience in teaching within the PhD curriculum at the Faculty of Health Sciences. He was chairman of the Danish Society for Theoretical Statistics from 1996 to 2000. Peter Dalgaard has been a key member of the R Core Team since August 1997 and is well known among R users.