Eco-Stats: Data Analysis in Ecology: From T-Tests to Multivariate Abundances - Rilegato

Warton, David I.

Rilegato

ISBN 10: 3030884422 ISBN 13: 9783030884420

Casa editrice: Springer Nature, 2022

Riassunto

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.

Su questo libro

Informazioni sull?autore

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.

Dalla quarta di copertina

This book introduces ecologists to the wonderful world of modern tools for data analysis, especially multivariate analysis.

Assuming only a vague recollection of an introductory statistics course, 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.  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.  Maths 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 and data can be found in the ecostats R package on CRAN.

• For biologists with relatively little prior knowledge of statistics - introducing a modern, advanced approach to data analysis in an intuitive and accessible way
• Introduces modern methods of multivariate analysis to ecology - as direct extensions of univariate techniques

Introduces a range of advanced statistics topics relevant to the modern ecologist - including mixed models, model selection, design-based inference, spatial statistics, latent variable models.

David Warton, PhD, 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 of identifying core concepts and packaging them in ways that people who don’t share his insight can understand.

 

Dettagli dell?edizione

• Editore: Springer Nature
• Data di pubblicazione: 2022
• ISBN 10: 3030884422
• ISBN 13: 9783030884420
• Rilegatura: Copertina rigida
• Lingua: Inglese
• Numero edizione: 1
• Numero di pagine: 433
• Contatto del produttore: non disponibile