An Introduction to R: Data Analysis and Visualization

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. 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.

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An Introduction to R: Data Analysis and Visualization

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. 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.

50.0 In Stock
An Introduction to R: Data Analysis and Visualization

An Introduction to R: Data Analysis and Visualization

by Mark Gardener
An Introduction to R: Data Analysis and Visualization

An Introduction to R: Data Analysis and Visualization

by Mark Gardener

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$50.00 
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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. 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.


Product Details

ISBN-13: 9781784273385
Publisher: Pelagic Publishing
Publication date: 06/14/2023
Series: Research Skills
Pages: 384
Product dimensions: 6.77(w) x 9.42(h) x 0.86(d)

About the Author

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

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
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