An Introduction to R: Data Analysis and Visualization

by Mark Gardener

Overview

The modern world is awash with data. The R Project is a statistical environment and programming language that can help to make sense of it all. A huge open-source project, R has become enormously popular because of its power and flexibility. With R you can organise, analyse and visualise data. This clear and methodical book will help you learn how to use R from the ground up, giving you a start in the world of data science.

Learning about data is important in many academic and business settings, and R offers a potent and adaptable programming toolbox. The book covers a range of topics, including: importing/exporting data, summarising data, visualising data, managing and manipulating data objects, data analysis (regression, ANOVA and association among others) and programming functions. Regardless of your background or specialty, you'll find this book the perfect primer on data analysis, data visualisation and data management, and a springboard for further exploration.

Product Details

ISBN-13:	9781784273392
Publisher:	Pelagic Publishing
Publication date:	05/23/2023
Series:	Research Skills
Sold by:	Barnes & Noble
Format:	eBook
File size:	3 MB

About the Author

Mark Gardener is a self-employed scientist and consultant, with a PhD in ecology. He provides data analysis and consultancy across a wide range of disciplines. Mark specialises in the use of the R Project for Statistical Computing.

Mark Gardener began his career as an optician but returned to science and trained as an ecologist. His research is in the area of pollination ecology. He has worked extensively in the UK as well as Australia and the United States. Currently he works as an associate lecturer for the Open University and also runs courses in data analysis for ecology and environmental science.

Table of Contents

1. A brief introduction to R
2. Basic math
3. Introduction to R objects
4. Making and importing data objects
5. Managing and exporting data objects
6. R object types and their properties
7. Working with data objects
8. Manipulating data objects
9. Summarizing data
10. Tabulation
11. Graphics: basic charts
12. Graphics: adding to plots
13. Graphics: advanced methods
14. Analyze data: statistical analyses
15. Programming tools
Appendix
Index