Overview
- Written for biologists with relatively little prior knowledge of statistics
- Introduces modern methods of multivariate analysis to ecology as direct extensions of univariate techniques
- Discusses a range of advanced statistics topics relevant to the modern ecologist
Part of the book series: Methods in Statistical Ecology (MISE)
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Table of contents (18 chapters)
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Front Matter
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Regression Analysis for a Single Response Variable
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Front Matter
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Regression Analysis for Multiple Response Variables
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Front Matter
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Regression Analysis for Multivariate Abundances
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Front Matter
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Keywords
About this book
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.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Eco-Stats: Data Analysis in Ecology
Book Subtitle: From t-tests to Multivariate Abundances
Authors: David I Warton
Series Title: Methods in Statistical Ecology
DOI: https://doi.org/10.1007/978-3-030-88443-7
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-88442-0Published: 12 August 2022
Softcover ISBN: 978-3-030-88445-1Published: 13 August 2023
eBook ISBN: 978-3-030-88443-7Published: 10 August 2022
Series ISSN: 2199-319X
Series E-ISSN: 2199-3203
Edition Number: 1
Number of Pages: XII, 433
Number of Illustrations: 28 b/w illustrations, 109 illustrations in colour
Topics: Statistical Theory and Methods, Biostatistics, Community & Population Ecology, Statistics for Life Sciences, Medicine, Health Sciences, Animal Ecology, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences