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Informationen zum Autor Murray Logan is a lecturer and researcher in the School of Biological Sciences, Monash University, Melbourne, Australia. He teaches a range of zoological and ecological courses in addition to biostatistical and R courses to undergraduate and graduate students. He also provides research design and analysis advice to a range of university, government and private organizations. Klappentext R - the statistical and graphical environment is rapidly emerging as an important set of teaching and research tools for biologists. This book draws upon the popularity and free availability of R to couple the theory and practice of biostatistics into a single treatment, so as to provide a textbook for biologists learning statistics, R, or both. An abridged description of biostatistical principles and analysis sequence keys are combined together with worked examples of the practical use of R into a complete practical guide to designing and analyzing real biological research. Topics covered include: simple hypothesis testing, graphing exploratory data analysis and graphical summaries regression (linear, multi and non-linear) simple and complex ANOVA and ANCOVA designs (including nested, factorial, blocking, spit-plot and repeated measures) frequency analysis and generalized linear models. Linear mixed effects modeling is also incorporated extensively throughout as an alternative to traditional modeling techniques. The book is accompanied by a companion website www.wiley.com/go/logan/r with an extensive set of resources comprising all R scripts and data sets used in the book, additional worked examples, the biology package, and other instructional materials and links. Zusammenfassung First book specifically aimed at biologists/ecologists thatexplains how the new freeware statistical package R can be applied to their problems. This software package is becoming increasingly popular as it ispowerful and free. Inhaltsverzeichnis Preface xv R quick reference card xix General key to statistical methods xxvii 1 Introduction to R 1 1.1 Why R? 1 1.2 Installing R 2 1.2.1 Windows 2 1.2.2 Unix/Linux 2 1.2.3 MacOSX 3 1.3 The R environment 3 1.3.1 The console (command line) 4 1.4 Object names 4 1.5 Expressions, Assignment and Arithmetic 5 1.6 R Sessions and workspaces 6 1.6.1 Cleaning up 6 1.6.2 Workspaces 7 1.6.3 Current working directory 7 1.6.4 Quitting R 8 1.7 Getting help 8 1.8 Functions 9 1.9 Precedence 10 1.10 Vectors - variables 11 1.10.1 Regular or patterned sequences 12 1.10.2 Character vectors 13 1.10.3 Factors 15 1.11 Matrices, lists and data frames 16 1.11.1 Matrices 16 1.11.2 Lists 17 1.11.3 Data frames - data sets 18 1.12 Object information and conversion 18 1.12.1 Object information 18 1.12.2 Object conversion 20 1.13 Indexing vectors, matrices and lists 20 1.13.1 Vector indexing 21 1.13.2 Matrix indexing 22 1.13.3 List indexing 23 1.14 Pattern matching and replacement (character search and replace) 24 1.14.1 grep - pattern searching 24 1.14.2 regexpr - position and length of match 25 1.14.3 gsub - pattern replacement 26 1.15 Data manipulation 26 1.15.1 Sorting 26 1.15.2 Formatting data 27 1.16 Functions that perform other functions repeatedly 28 1.16.1 Along matrix margins 29 1.16.2 By factorial groups 30 1.16.3 By objects 30 1.17 Programming in R 30 1.17.1 Grouped expressions 31 1.17.2 Conditional execution - if and ifelse 31 1.17.3 Repeated execution - looping 32 1.17.4 Writing functions 34 1.18 An introduction to the R graphical environment 35 1.18.1 The ...
