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Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. To avoid the difficulty of teaching R and statistics at the same time, statistical methods are kept to a minimum. The text covers how to download and install R, import and manage data, elementary plotting, an introduction to functions, advanced plotting, and common beginner mistakes. This book contains everything you need to know to get started with R. "Its biggest advantage is that it aims only to teach R...It organizes R commands very efficiently, with much teaching guidance included. I would describe this book as being handy--it's the kind of book that you want to keep in your jacket pocket or backpack all the time, ready for use, like a Swiss Army knife." (Loveday Conquest, University of Washington) "Whilst several books focus on learning statistics in R..., the authors of this book fill a gap in the market by focusing on learning R whilst almost completely avoiding any statistical jargon...The fact that the authors have very extensive experience of teaching R to absolute beginners shines throughout." (Mark Mainwaring, Lancaster University) "Exactly what is needed...This is great, nice work. I love the ecological/biological examples; they will be an enormous help." (Andrew J. Tyne, University of Nebraska-Lincoln) Alain F. Zuur is senior statistician and director of Highland Statistics Ltd., a statistical consultancy company based in the UK. He has taught statistics to more than 5000 ecologists. He is honorary research fellow in the School of Biological Sciences, Oceanlab, at the University of Aberdeen, UK. Elena N. Ieno is senior marine biologist and co-director at Highland Statistics Ltd. She has been involved in guiding PhD students on the design and analysis of ecological data. She is honorary research fellow in the School of Biological Sciences, Oceanlab, at the University of Aberdeen, UK. Erik H.W.G. Meesters is a researcher at the Dutch Institute for Marine Resources and Ecosystem Studies (IMARES). He specializes in coral reef ecology and applied statistics and conducts research on North Sea benthos and seal ecology.

Mathematical statistics --Data processing --Handbooks, manuals, etc. --- R (Computer program language) --Handbooks, manuals, etc. --- R (Computer program language) --- Mathematical statistics --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Data processing --- Science --- Statistics --- Statistical methods --- Statistical analysis --- Statistical data --- Statistical science --- Natural science --- Science of science --- Sciences --- Mathematical statistics. --- Ecology. --- Statistics. --- Statistics and Computing/Statistics Programs. --- Theoretical Ecology/Statistics. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Econometrics --- Balance of nature --- Biology --- Bionomics --- Ecological processes --- Ecological science --- Ecological sciences --- Environment --- Environmental biology --- Oecology --- Environmental sciences --- Population biology --- Statistical inference --- Statistics, Mathematical --- Probabilities --- Sampling (Statistics) --- Ecology --- GNU-S (Computer program language) --- Domain-specific programming languages --- Statistics . --- Ecology . --- R (Computer program language). --- Biometry. --- Statistics and Computing. --- Theoretical and Statistical Ecology. --- Biostatistics. --- Data processing. --- Biological statistics --- Biometrics (Biology) --- Biostatistics --- Biomathematics

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Regression analysis --- Multilevel models (Statistics) --- Analyse de régression --- Modèles multiniveaux (Statistique) --- Analyse de régression --- Modèles multiniveaux (Statistique)

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This book presents Generalized Linear Models (GLM) and Generalized Linear Mixed Models (GLMM) based on both frequency-based and Bayesian concepts. Using ecological data from real-world studies, the text introduces the reader to the basics of GLM and mixed effects models, with demonstrations of binomial, gamma, Poisson, negative binomial regression, and beta and beta-binomial GLMs and GLMMs. The book uses the functions glm, lmer, glmer, glmmADMB, and also JAGS from within R. JAGS results are compared with frequentist results. R code to construct, fit, interpret, and comparatively evaluate models is provided at every stage. Otherwise challenging procedures are presented in a clear and comprehensible manner with each step of the modelling process explained in detail, and all code is provided so that it can be reproduced by the reader.

Ecology --- Linear models (Statistics) --- Generalized estimating equations --- Multilevel models (Statistics) --- R (Computer program language) --- Ecology --- Bayes Theorem --- Data Interpretation, Statistical --- Linear Models --- Software --- Statistical methods

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Biomathematics. Biometry. Biostatistics --- Computer. Automation --- medische statistiek --- biostatistiek --- informatica --- statistiek --- ecologie --- biometrie