An Introduction to R - Data Analysis and Visualization

Everything about Popular Science EN

€44,43 1 In stock: Ordered on working days before 17:00, shipped the same day.

Useful for beginners and also as a reference for more seasoned veterans.
Plenty of examples throughout, as well as additional notes and tips.
Chapter summaries in concise table format help the book to be used as an ongoing reference work.... Show more

Gratis verzending in Nederland vanaf €50,-*
Ordered before 5 p.m. on working days? Shipped the same day!
14-day money back guarantee
We are happy to think along!

Product description

Author	Mark Gardener
Language	English
ISBN	9781784273385
Publisher	Pelagic Publishing
Pages	384
Format	Paperback
Images	Figures and tables
Year published	2023

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.

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