New Statistics With R - An Introduction for Biologists

A proven textbook based on materials developed over the last decade to teach linear, generalized, and mixed model analysis to students of ecology, evolution, and environmental studies. While R is used throughout, the focus is firmly on statistical analysis.

List of contents

• 1: Introduction


• 2: Motivation


• 3: Description


• 4: Reproducible Research


• 5: Estimation


• 6: Linear Models


• 7: Regression


• 8: Prediction


• 9: Testing


• 10: Intervals


• 11: Analysis of Variance


• 12: Factorial Designs


• 13: Analysis of Covariance


• 14: Linear Model Complexities


• 15: Generalized Linear Models


• 16: GLMs for Count Data


• 17: Binomial GLMs


• 18: GLMs for Binary Data


• 19: Conclusions


• 20: A Very Short Introduction to R

About the author

Andy Hector is Professor of Ecology at the Department of Plant Sciences, Linacre College, University of Oxford, UK. He is Co-Director of the Plants for the Twenty-First Century Institute. He has convened and taught statistics on the Quantitative Methods for Biologists course for undergraduates. He is a community ecologist interested in biodiversity loss and its consequences for ecosystem functioning, stability and services and scientific PI of the Sabah Biodiversity Experiment. He has contributed to several publications on ecological analysis.

Summary

A proven textbook based on materials developed over the last decade to teach linear, generalized, and mixed model analysis to students of ecology, evolution, and environmental studies. While R is used throughout, the focus is firmly on statistical analysis.

Product details

• Authors: Andy Hector, Andy (Professor of Ecology Hector, Hector Andy
• Publisher: Oxford University Press
• Languages: English
• Product format: Paperback / Softback
• Released: 17.06.2021
• EAN: 9780198798187
• ISBN: 978-0-19-879818-7
• No. of pages: 278
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; MATHEMATICS / Probability & Statistics / General, SCIENCE / Life Sciences / Biology, MATHEMATICS / Applied, Biology, life sciences, Programming Techniques, Mathematical & statistical software, Program concepts / learning to program, Mathematical and statistical software, Data capture and analysis, Data Capture & Analysis