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Cover

Insights from Data with R

An Introduction for the Life and Environmental Sciences

Owen L. Petchey, Andrew P. Beckerman, Natalie Cooper, and Dylan Z. Childs

February 2021

ISBN: 9780198849827

320 pages
Paperback
240x168mm

In Stock

Price: £27.99

This accessible and engaging book provides readers with the knowledge, experience, and confidence to work with raw data and unlock essential information (insights) from data summaries and visualisations.

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Description

This accessible and engaging book provides readers with the knowledge, experience, and confidence to work with raw data and unlock essential information (insights) from data summaries and visualisations.

  • The go-to introductory R data book for life and environmental science undergraduates and their teachers, with no background in statistics or programming being required
  • Adopts an approach to R based on the “tidyverse” packages, providing efficient, reliable, and confidence-inspiring methods and workflow
  • Features a set of Workflow Demonstrations fully accessible to the reader and utilising data collected in real-life studies.
  • Based on a proven and successful introductory data analysis course, featuring the same author team as the hugely popular Getting Started with R: An Introduction for Biologists

About the Author(s)

Owen L. Petchey, Professor of Integrative Ecology, Department of Evolutionary Biology and Environmental Studies, University of Zürich, Switzerland, Andrew P. Beckerman, Professor of Evolutionary Ecology, Department of Animal and Plant Sciences, University of Sheffield, UK, Natalie Cooper, Researcher in Life Sciences, Natural History Museum, London, UK, and Dylan Z. Childs, Senior Lecturer, Department of Animal and Plant Sciences, University of Sheffield, UK

Owen L. Petchey is Professor of Integrative Ecology at the Department of Evolutionary Biology and Environmental Studies, University of Zürich, Switzerland. He has used R for nearly 20 years, and has particular expertise in teaching beginners, multivariate statistics, spatial data, programming, maximum likelihood estimation, and visualisation (i.e., nice graphs!). His research focuses on the causes and consequences of extinctions in a changing world. His group performs experiments with microbial communities, models the structure of food webs, analyses variation in biodiversity, and does fieldwork in Iceland, the UK, and Switzerland.

Andrew P. Beckerman is Professor of Evolutionary Ecology at the Department of Animal and Plant Sciences, University of Sheffield, UK. He has used R for nearly 20 years, and has particular expertise in teaching the exploration, visualisation and analysis of simple and complex data. His research focuses on the structure and dynamics of ecological communities facing multiple simultaneous stressors. His group models the structure and dynamics of food webs, analyses trait and population responses to environmental variation, and explores the conservation ecology of endangered species.

Natalie Cooper is a Researcher at the Natural History Museum, London, UK, where her research focuses on understanding the evolution of biodiversity. She works on all kinds of organisms, from parasites to blue whales, and does all of her research in R.

Dylan Z. Childs is a Senior Lecturer at the University of Sheffield, UK. He has used R for over 15 years and has particular expertise in teaching population modelling and advanced statistical tools such as mixed models. His research focuses on data-driven modelling of populations and communities. His group uses demographic methods to model structured population dynamics, analyses trait and population responses to environmental variation, and develops methods for integrating individual- and population-level data into predictive models.

Table of Contents

    Preface
    1:Introduction
    2:Getting acquainted
    3:Workflow demonstration Part 1: Preparation
    4:Workflow demonstration Part 2: Getting insights
    5:Dealing with data 1: Digging into dplyr
    6:Dealing with data 2: Expanding your toolkit
    7:Getting to grips with ggplot2
    8:Making Deeper Insights Part 1: Working with single variables
    9:Making Deeper Insights Part 2: Relationships among (many) variables
    10:Looking back and looking forward

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