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"Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research.This edition: Features full colour text and extensive graphics throughout. Introduces a clear structure with numbered section headings to help readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis and Meta-Analysis. Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user. Praise for the first edition:'...if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.' (The American Statistician, August 2008)'The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book...' (Professional Pensions, July 2007) "-- "This edition introduces the advantages of the R environment, in a user-friendly format, to beginners and intermediate users in a range of disciplines, from science and engineering to medicine and economics"--
Programming --- Computer assisted instruction --- Mathematical statistics --- Traitement des données --- Data processing --- Méthode statistique --- Statistical methods --- Application des ordinateurs --- computer applications --- Analyse de données --- Data analysis --- Logiciel --- Computer software --- R (Computer program language) --- Data processing. --- MET Methods & Techniques --- Computer program languages --- -681.3*G3 --- 004 --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- 681.3*G3 Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- #SBIB:303H520 --- #SBIB:303H4 --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Informatica in de sociale wetenschappen --- 681.3*G3 --- GNU-S (Computer program language) --- Domain-specific programming languages
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Animal ethology and ecology. Sociobiology --- Animal parasites --- Animals--Parasites --- Animaux predateurs --- Biologie des populations --- Biologie van de populaties --- Diseases --- Epizoa --- Human beings--Diseases --- Illness --- Illnesses --- Maladies --- Morbidity --- Parasieten --- Parasites --- Parasitism --- Parasitisme --- Populaties [Biologie van de ] --- Population biology --- Populations [Biologie des ] --- Predation (Biology) --- Predator-prey relations --- Predatory animals --- Predatory behavior (Biology) --- Preying (Biology) --- Proies et prédateurs --- Prédateurs et proies --- Prédation (Biologie) --- Relations proie-prédateur --- Relations prédateur-proie --- Roofdieren --- Roven (Biologie) --- Sickness --- Sicknesses --- Ziekten --- Disease --- Pest Control, Biological --- Population Dynamics --- Predatory Behavior --- Pests --- Animaux et plantes nuisibles, Lutte biologique contre les --- Biological control --- -576.8 --- Animal pests --- Pest animals --- Vermin --- Organisms --- Biology, Economic --- Zoology, Economic --- Human beings --- Medicine --- Epidemiology --- Health --- Pathology --- Sick --- Animals --- Parasitic animals --- Parasitic organisms --- Parasitology --- Biology --- Ecology --- Predaceous animals --- Predacious animals --- Predators --- Communities, Predator-prey --- Dynamics, Predator-prey --- Interactions, Predator-prey --- Predator-prey communities --- Predator-prey dynamics --- Predator-prey interactions --- Predator-prey relationships --- Predator-prey systems --- Predators and prey --- Predatory-prey relationships --- Prey and predators --- Prey-predator relationships --- Relations, Predator-prey --- Relationships, Predator-prey --- Systems, Predator-prey --- Animal ecology --- Food --- Diseases. --- Parasites. --- Parasitism. --- Population biology. --- Predatory animals. --- Biological control. --- Predation (Biology). --- 576.8 Parasitology --- Prédation (Biologie) --- 576.8 --- Bio-control of pests --- Biocontrol of pests --- Biological control of pests --- Biological pest control --- Biological pest control agents --- Control --- Disease. --- Pest Control, Biological. --- Population Dynamics. --- Predatory Behavior. --- Pests - Biological control.
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The high-level language of R is recognized as one of the most powerful and flexible statistical software environments, and is rapidly becoming the standard setting for quantitative analysis, statistics and graphics. R provides free access to unrivalled coverage and cutting-edge applications, enabling the user to apply numerous statistical methods ranging from simple regression to time series or multivariate analysis. Building on the success of the author's bestselling Statistics: An Introduction using R, The R Book is packed with worked examples, providing an all inclusive guide to R, ideal for novice and more accomplished users alike. The book assumes no background in statistics or computing and introduces the advantages of the R environment, detailing its applications in a wide range of disciplines. Provides the first comprehensive reference manual for the R language, including practical guidance and full coverage of the graphics facilities. Introduces all the statistical models covered by R, beginning with simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression and analysis of variance, through to generalized linear models, generalized mixed models, time series, spatial statistics, multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates and professionals in science, engineering and medicine. It is also ideal for students and professionals in statistics, economics, geography and the social sciences.
Programming --- Mathematical statistics --- R (Computer program language) --- Data processing --- R (Computer program language). --- Data processing. --- regressie-analyse --- softwarepakketten --- tijdreeksanalyse --- wiskundige statistiek --- 681.3*G3 --- 681.3*G3 Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- GNU-S (Computer program language) --- Domain-specific programming languages --- R (Langage de programmation) --- Statistique mathématique --- Informatique --- Mathematical statistics - Data processing
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Botany --- Botanique --- Ecology --- Ecologie --- Phytoécologie --- plant ecology --- Population végétale --- plant population --- Couverture végétale --- Plant cover --- Dynamique des populations --- population dynamics --- Forêt tropicale --- Tropical forests --- Ressource génétique --- genetic resources --- Photosynthèse --- Photosynthesis --- Variation génétique --- genetic variation --- Composition botanique --- Botanical composition --- Pollinisation --- Pollination --- Dissémination des graines --- seed dispersal --- Plant ecology. --- Planten : ecologie --- 581.5 --- Plant ecology --- Plants --- Phytoecology --- Vegetation ecology --- Floristic ecology --- DYNAMICS --- PHOTOSYNTHESIS --- DEVELOPMENT --- GROWTH --- LIFE HISTORY --- BREEDING --- SEED DISPERSAL --- POLLINATION --- PLANTS --- POPULATIONS --- PANAMA --- TROPICAL TREES --- CANOPY GAPS --- COMPETITION --- RESOURCES --- PLANT COMMUNITIES --- PLANT ECOLOGY --- TEXTBOOKS
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Ecology --- Linear models (Statistics) --- Statistical methods --- Data processing. --- -Linear models (Statistics) --- GLIM. --- Environmental Sciences and Forestry. Ecology -- Ecology (General) --- Environmental Sciences and Forestry Ecology -- Ecology (General). --- #WDIR:wbse --- 519.242 --- 57.087.1 --- 574 --- 57.087.1 Biometry. Statistical study and treatment of biological data --- Biometry. Statistical study and treatment of biological data --- 574 General ecology. Biocoenology. Hydrobiology. Biogeography --- General ecology. Biocoenology. Hydrobiology. Biogeography --- 519.242 Experimental design. Optimal designs. Block designs --- Experimental design. Optimal designs. Block designs --- Models, Linear (Statistics) --- Mathematical models --- Mathematical statistics --- Statistics --- Balance of nature --- Biology --- Bionomics --- Ecological processes --- Ecological science --- Ecological sciences --- Environment --- Environmental biology --- Oecology --- Environmental sciences --- Population biology --- Statistical methods&delete& --- Data processing --- Biomathematics. Biometry. Biostatistics --- Programming --- General ecology and biosociology --- Ecology - Statistical methods - Data processing. --- Linear models (Statistics) - Data processing. --- Ecology-statistical methods-data processing --- Linear models(Statistics)-data processing
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Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing. Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology. Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. Covers the full range of statistical techniques likely to be need 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. Accompanied by a website featuring worked examples, data sets, exercises and solutions: http://www.imperial.ac.uk/bio/research/crawley/statistics Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology & but wi
Computer industry: markets; standards; statistics; suppliers --- Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- 681.3*G3 Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- 681.3*K1 Computer industry: markets; standards; statistics; suppliers --- Mathematical statistics --- R (Computer program language) --- 681.3*D3 --- 681.3*G3 --- 681.3*I25 --- 681.3*J2 --- 681.3*K1 --- GNU-S (Computer program language) --- Domain-specific programming languages --- 681.3*D3 Programming languages --- Programming languages --- 681.3*J2 Physical sciences and engineering (Computer applications) --- Physical sciences and engineering (Computer applications) --- 681.3*I25 Programming languages and software: expert system tools and techniques (Artificial intelligence)--See also {681.3*D32} --- Programming languages and software: expert system tools and techniques (Artificial intelligence)--See also {681.3*D32} --- Programming --- R (Computer program language). --- Statistique mathématique --- R (Langage de programmation) --- Textbooks --- Manuels d'enseignement supérieur --- Mathematical statistics - Textbooks --- Acqui 2006
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Quantitative methods in social research --- Mathematical statistics --- Programming
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Get inside Japan''s invisible behemoth to see the future of global business Good Risks is a fascinating insight into ORIX, a global giant whose business empire straddles the world, but which has managed to remain out of the media spotlight for half a century. Award winning author David Russell explains how this Japanese company has transcended its national identity to become a global player, and what that means for everyone else. In a series of one-on-one interviews with senior executives at ORIX companies around the world, readers gain a firsthand glimpse of the inner workings of this ""invis
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