Del i serien Chapman & Hall/CRC The R Series

R for Conservation and Development Projects

A Primer for Practitioners

Inbunden, Engelska, 2020

AvNathan Whitmore

3 009 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

Finns i fler format (1)

Häftad

1 189 kr

Skickas inom 10-15 vardagar

This book is aimed at conservation and development practitioners 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

Produktinformation

Utgivningsdatum2020-12-22
Mått156 x 234 x 26 mm
Vikt680 g
FormatInbunden
SpråkEngelska
SerieChapman & Hall/CRC The R Series
Antal sidor390
FörlagTaylor & Francis Ltd
ISBN9780367205492

Tillhör följande kategorier

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

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