« ...I know of no better book of its kind... » (Journal of the Royal Statistical Society, Vol 169 (1), Janvier 2006)
Une édition révisée et mise à jour de ce manuel d'introduction à l'analyse statistique le plus vendu en utilisant le logiciel libre leader R
Cette nouvelle édition d'un titre à succès offre une introduction concise à un large éventail de méthodes statistiques, à un niveau suffisamment élémentaire pour plaire à un large éventail de disciplines. Les instructions étape par étape aident le non-statisticien à comprendre pleinement la méthodologie. Le livre couvre toute la gamme des techniques statistiques susceptibles d'être nécessaires pour analyser les données des projets de recherche, y compris le matériel élémentaire comme les tests t - et les tests chi - carré, les méthodes intermédiaires comme la régression et l'analyse de la variance, et des techniques plus avancées comme la modélisation linéaire généralisée.
Comprend de nombreux exemples et exercices travaillés dans chaque chapitre.
A revised and updated edition of this bestselling introduction to statistical analysis using the leading free software package R In recent years R has become one of the most popular, powerful and flexible statistical software packages available. It enables users to apply a wide variety of statistical methods, ranging from simple regression to generalized linear modelling, and has been widely adopted by life scientists and social scientists. This new edition 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 such as t tests and chi–squared tests, intermediate methods such as regression and analysis of variance, and more advanced techniques such as generalized linear modelling. Numerous worked examples and exercises are included within each chapter. Comprehensively revised to include more detailed introductory material on working with R Updated to be compatible with the current R Version 3 Complete coverage of all the essential statistical methods Focus on linear models (regression, analysis of variance and analysis of covariance) and generalized linear models (for count data, proportion data and age–at–death data) Now includes more detail on experimental design Accompanied by a website featuring worked examples, data sets, exercises and solutions www.imperial.ac.uk/bio/research/crawley/statistics Statistics: An introduction using R is primarily aimed at undergraduate students in medicine, engineering, economics and biology but will also appeal to postgraduates in these areas who wish to switch to using R.
