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Synopsis
This book introduces ecologists to the wonderful world of modern tools for data analysis, especially multivariate analysis.
For biologists with relatively little prior knowledge of statistics, it introduces a modern, advanced approach to data analysis in an intuitive and accessible way. The book begins by reviewing some core principles in statistics, and relates common methods to the linear model, a general framework for modeling data where the response is continuous. This is then extended to discrete data using generalized linear models, to designs with multiple sampling levels via mixed models, and to situations where there are multiple response variables via model-based approaches to multivariate analysis. Along the way there is an introduction to: important principles in model selection; adaptations of the model to handle non-linearity and cyclical variables; dependence due to structured correlation in time, space or phylogeny; and design-based techniques for inference that can relax some of the modelling assumptions. It concludes with a range of advanced topics in model-based multivariate analysis relevant to the modern ecologist, including fourth corner, latent variable and copula models.
Examples span a variety of applications including environmental monitoring, species distribution modeling, global-scale surveys of plant traits, and small field experiments on biological controls. Math Boxes throughout the book explain some of the core ideas mathematically for readers who want to delve deeper, and R code is used throughout. Accompanying code, data, and solutions to exercises can be found in the ecostats R package on CRAN.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
David Warton is professor and leads the Eco-Stats group based in the School of Mathematics and Statistics and is affiliated with the Evolution & Ecology Research Centre at the University of New South Wales (Australia). He is an ecological statistician who advances methodology for data analysis in ecology and is one of quantitative ecology's great explainers. He has an unerring knack for identifying core concepts and packaging them in comprehensible ways.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Eco-Stats: Data Analysis in Ecology
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Springer, Berlin|Springer International Publishing|Springer, 2023
ISBN 10 : 3030884457
ISBN 13 : 9783030884451
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book introduces ecologists to the wonderful world of modern tools for data analysis, especially multivariate analysis.For biologists with relatively little prior knowledge of statistics, it introduces a modern, advanced approach to data analy. N° de réf. du vendeur 945397991
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Eco-Stats: Data Analysis in Ecology: From t-tests to Multivariate Abundances (Methods in Statistical Ecology)
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Eco-Stats: Data Analysis in Ecology
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ISBN 10 : 3030884457
ISBN 13 : 9783030884451
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces ecologists to the wonderful world of modern tools for data analysis, especially multivariate analysis.For biologists with relatively little prior knowledge of statistics, it introduces a modern, advanced approach to data analysis in an intuitive and accessible way. The book begins by reviewing some core principles in statistics, and relates common methods to the linear model, a general framework for modeling data where the response is continuous. This is then extended to discrete data using generalized linear models, to designs with multiple sampling levels via mixed models, and to situations where there are multiple response variables via model-based approaches to multivariate analysis. Along the way there is an introduction to: important principles in model selection; adaptations of the model to handle non-linearity and cyclical variables; dependence due to structured correlation in time, space or phylogeny; and design-based techniques for inference that can relax some of the modelling assumptions.It concludes with a range of advanced topics in model-based multivariate analysis relevant to the modern ecologist, including fourth corner, latent variable and copula models.Examples span a variety of applications including environmental monitoring, species distribution modeling, global-scale surveys of plant traits, and small field experiments on biological controls. Math Boxes throughout the book explain some of the core ideas mathematically for readers who want to delve deeper, and R code is used throughout.Accompanying code, data, and solutions to exercises can be found in the ecostats R package on CRAN. 448 pp. Englisch. N° de réf. du vendeur 9783030884451
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Eco-Stats: Data Analysis in Ecology : From t-tests to Multivariate Abundances
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Springer International Publishing, Springer Nature Switzerland, 2023
ISBN 10 : 3030884457
ISBN 13 : 9783030884451
Neuf
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces ecologists to the wonderful world of modern tools for data analysis, especially multivariate analysis.For biologists with relatively little prior knowledge of statistics, it introduces a modern, advanced approach to data analysis in an intuitive and accessible way. The book begins by reviewing some core principles in statistics, and relates common methods to the linear model, a general framework for modeling data where the response is continuous. This is then extended to discrete data using generalized linear models, to designs with multiple sampling levels via mixed models, and to situations where there are multiple response variables via model-based approaches to multivariate analysis. Along the way there is an introduction to: important principles in model selection; adaptations of the model to handle non-linearity and cyclical variables; dependence due to structured correlation in time, space or phylogeny; and design-based techniques for inference that can relax some of the modelling assumptions.It concludes with a range of advanced topics in model-based multivariate analysis relevant to the modern ecologist, including fourth corner, latent variable and copula models.Examples span a variety of applications including environmental monitoring, species distribution modeling, global-scale surveys of plant traits, and small field experiments on biological controls. Math Boxes throughout the book explain some of the core ideas mathematically for readers who want to delve deeper, and R code is used throughout.Accompanying code, data, and solutions to exercises can be found in the ecostats R package on CRAN. N° de réf. du vendeur 9783030884451
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Eco-Stats: Data Analysis in Ecology
ISBN 10 : 3030884457
ISBN 13 : 9783030884451
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book introduces ecologists to the wonderful world of modern tools for data analysis, especially multivariate analysis.For biologists with relatively little prior knowledge of statistics, it introduces a modern, advanced approach to data analysis in an intuitive and accessible way. The book begins by reviewing some core principles in statistics, and relates common methods to the linear model, a general framework for modeling data where the response is continuous. This is then extended to discrete data using generalized linear models, to designs with multiple sampling levels via mixed models, and to situations where there are multiple response variables via model-based approaches to multivariate analysis. Along the way there is an introduction to: important principles in model selection; adaptations of the model to handle non-linearity and cyclical variables; dependence due to structured correlation in time, space or phylogeny; and design-based techniques for inference that can relax some of the modelling assumptions. It concludes with a range of advanced topics in model-based multivariate analysis relevant to the modern ecologist, including fourth corner, latent variable and copula models.Examples span a variety of applications including environmental monitoring, species distribution modeling, global-scale surveys of plant traits, and small field experiments on biological controls. Math Boxes throughout the book explain some of the core ideas mathematically for readers who want to delve deeper, and R code is used throughout. Accompanying code, data, and solutions to exercises can be found in the ecostats R package on CRAN.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 448 pp. Englisch. N° de réf. du vendeur 9783030884451
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Eco-stats - Data Analysis in Ecology: From T-tests to Multivariate Abundances
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