Michael J. Crawley

A start-to-finish guide to one of the most useful programming languages for researchers in a variety of fields In the newly revised Third Edition of The R Book, a team of distinguished teachers and researchers delivers a user-friendly and comprehensive discussion of foundational and advanced topics in the R software language, which is used widely in science, engineering, medicine, economics, and other fields. The book is designed to be used as both a complete text—readable from cover to cover—and as a reference manual for practitioners seeking authoritative guidance on particular topics. This latest edition offers instruction on the use of the RStudio GUI, an easy-to-use environment for those new to R. It provides readers with a complete walkthrough of the R language, beginning at a point that assumes no prior knowledge of R and very little previous knowledge of statistics. Readers will also find: A thorough introduction to fundamental concepts in statistics and step-by-step roadmaps to their implementation in R;Comprehensive explorations of worked examples in R;A complementary companion website with downloadable datasets that are used in the book;In-depth examination of essential R packages. Perfect for undergraduate and postgraduate students of science, engineering, medicine economics, and geography, The R Book will also earn a place in the libraries of social sciences professionals.

"...I know of no better book of its kind..." (Journal of the Royal Statistical Society, Vol 169 (1), January 2006) A revised and updated edition of this bestselling introductory textbook to statistical analysis using the leading free software package R This new edition of a bestselling title offers a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a wide range of disciplines. Step-by-step instructions help the non-statistician to fully understand the methodology. The book covers the full range of statistical techniques likely to be needed to analyse the data from research projects, including elementary material like t--tests and chi--squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. Includes numerous worked examples and exercises within each chapter.

R ist als statistische Standard-Programmiersprache für viele zu einem unverzichtbaren Werkzeug für zahlreiche Techniken der statistischen Modellierung und Datenanalyse geworden. Sie ermöglicht eine breite Auswahl statistischer Methoden – von der einfachen Regression bis hin zu Generalisierten Linearen Modellen. Statistik mit R ist eine anschauliche und leicht nachvollziehbare Einführung in die statistische Analyse unter Verwendung dieser leistungsstarken und frei erhältlichen Software. Michael J. Crawley bietet dem Leser Schritt-für-Schritt-Anleitungen, die keine Programmiervorkenntnisse voraussetzen und die dem Nicht-Statistiker helfen, die Methodik vollständig zu verstehen. Mit Hilfe von Praxisbeispielen wird der Leser von den einfachst en Fällen, bei denen vor allem die Richtigkeit der getroffenen Annahmen überprüft wird (beispielsweise Konstanz einer Varianz, Normalverteilung von Fehlern), über Fälle, bei denen die Angemessenheit des gewählten Modells beurteilt wird, bis hin zu Fällen, die die Anpassung an die Daten behandeln, geführt. Außerdem deckt das Buch die volle Breite der statistischen Techniken ab, die üblicherweise für die Datenanalyse bei Forschungsarbeiten benötigt werden, zum Beispiel t-Tests, Chi-Quadrat-Tests, weiterführende Methoden wie Regression und Varianzanalyse und fortgeschrittene Techniken wie Generalisierte Lineare Modelle. Statistik mit R ist eine Einführung in ein breites Spektrum von statistischen Methoden, die in zahlreichen wissenschaftlichen Dis ziplinen Anwendung fi nden.

S-Plus is a first-rate graphical environment, used by thousands worldwide to perform basic, intermediate and advanced statistical analysis. It is remarkably powerful, yet relatively simple to use, once you have the basics at your fingertips. Statistical Computing: An Introduction to Data Analysis using S-Plus provides a pragmatic introduction to analysing data using S-Plus, whilst covering a huge breadth of topics, and assuming minimal statistical knowledge. *Provides an accessible yet comprehensive introduction to statistical computing, and can be used as a reference volume for S-Plus. *Covers a breadth of topics, including the basics, such as sampling and measures of central tendency and variation; the intermediate, such as analysis of variance and regression; and the most advanced modern methods, such as nonlinear mixed effects modelling and tree models. *Develops each concept from first principles in small steps, with worked examples and implementation advice throughout. *Assumes minimal experience of statistics and computing. *Emphasises graphical data inspection, parameter estimation and model criticism. *Supported by a Web site featuring all the data-frames, along with problems and worked examples. This is very much an introductory statistics book for all scientists. It is based on the premise that effective data analysis requires the mastery of a core of central ideas and methods, and that these cut across the boundaries of academic disciplines. It is suitable for advanced undergraduate, graduate students, researchers, and industry professionals from science, medicine, engineering, economics, the social sciences, and many other disciplines that have a need for statistical data analysis.

This book is about disease and death. It is an ecologist's view of Darwin's vivid evocation of Nature, red in tooth and claw. An international team of authors examines broad patterns in the population biology of natural enemies, and addresses general questions about the role of natural enemies in the population dynamics and evolution of their prey. For instance, how do large natural enemies like wolves differ from small natural enemies like bacterial diseases in their effects on prey abundance? Is it better to chase after prey, or sit and wait for it to come to you? How should prey behave in order to minimize the risk of being eaten? The answers are all in this fascinating senior undergraduate/postgraduate text.