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E-raamat: R for Conservation and Development Projects: A Primer for Practitioners

(Independent Environmental Consultant - Dunedin, New Zealand)
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"This book is aimed at conservation and development practitioners and who need to learn and use R in a part-time professional context. It gives people with a non-technical background a set of skills to graph, map, and model in R. It also provides background on data integration in project management and covers fundamental statistical concepts. The book aims to demystify R and give practitioners the confidence to use it"--

This book is aimed for conservation and development practitioners and who need to learn and use R in a part-time professional context. It gives people with a non-technical background a set of skills to graph, map, and model in R. It also provides background on data integration in project management and covers fundamental statistical concepts. The book aims to demystify R and give practitioners the confidence to use it.

Key Features:

• Viewing data science as part of a greater knowledge and decision making system
• Foundation sections on inference, evidence, and data integration
• Plain English explanations of R functions
• Relatable examples which are typical of activities undertaken by conservation and development organisations in the developing world
• Worked examples showing how data analysis can be incorporated into project reports

Arvustused

"The author leads the reader smoothly through the chapters of Part I and II, giving exactly as much information as is needed. This is the biggest advantage of the book. The new information and the R codes are given in a short but comprehensive and thoughtful way. With few words, the reader receives a message which is clear and easy to understand."

- Kinga Salapa, International Society for Clinical Biostatistics, 72, 2021

1. Introduction
2. Inference and Evidence
3. Data integration in project management
4. Getting started in R
5. Introduction to data frames
6. The Waihi project
7. ggplot2: graphing with the tidyverse
8. Customising a ggplot
9. Data wrangling
10. Data cleaning
11. Working with dates and time
12. Working with spatial data
13. Common R code mistakes and quirks
14. Basic statistical concepts
15. Understanding linear models
16. Extensions to linear models
17. Introduction to clustering and classification
18. Reporting and worked examples
19. Epilogue

Nathan Whitmore is a conservation scientist and practitioner who worked previously as a fisheries observer, and a ranger for the New Zealand Department of Conservation. Between 2012 and 2018 he worked in Papua New Guinea where he provided scientific and project support for the Wildlife Conservation Societys Papua New Guinea programme. His professional interests include evidence- based decision making, sustainable use of wildlife, and traditional natural resource management.