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- Title: R for Beginners
- Author(s) Sasha D. Hafner
- Publisher: Research Gate (August 2019)
- Paperback: N/A
- eBook: PDF (359 pages)
- Language: English
- ISBN-10: N/A
- ISBN-13: N/A
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The objective of this book is to introduce participants to the use of R for data manipulation and analysis. It is intended for individuals with little or no prior experience in R. The topics that are covered are those that author thinks are the most important for getting started with R. By the end of the book, you should be able to complete all steps reguired for data analysis and visualization using R, including the use of some relatively sophisticated methods.
About the Authors- N/A
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Hands-On Programming with R: Functions and Simulations
This book not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You’ll gain valuable programming skills and support your work as a data scientist at the same time.
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R Programming for Data Science (Roger D. Peng)
This book is about the fundamentals of R programming. Get started with the basics of the language, learn how to manipulate datasets, how to write functions, and how to debug and optimize code. You will have a solid foundation on data science toolbox.
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R Graphics Cookbook: Practical Recipes for Visualizing Data
This cookbook provides more than 150 recipes to help scientists, engineers, programmers, and data analysts generate high-quality graphs quickly - without having to comb through all the details of R's graphing systems.
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An Introduction to R (Alex Douglas, et al.)
The main aim of this book is to help you climb the initial learning curve and provide you with the basic skills and experience (and confidence!) to enable you to further your experience in using R.
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Advanced R, Second Edition (Hadley Wickham)
This book helps you understand how R works at a fundamental level. Designed for R programmers who want to deepen their understanding of the language, and programmers experienced in other languages to understand what makes R different and special.
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Advanced R Solutions (Malte Grosser, et al)
This book offers solutions to the exercises from Advanced R, 2nd Edition by Hadley Wickham. It is work in progress and under active development. The 2nd edition of Advanced R is in print now and we hope to provide most of the answers.
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R for Data Science: Visualize, Model, Transform, Tidy, Import
This book teaches you how to do data science with R: You'll learn how to get your data into R, get it into the most useful structure, transform it, visualize it and model it, how data science can help you work with the uncertainty and capture the opportunities.
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R Packages: Organize, Test, Document, and Share Your Code
Turn your R code into packages that others can easily download and use. This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author's package development philosophy.
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Forecasting, Principles and Practice, Using R (R. J. Hyndman)
This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly. Examples use R with many data sets taken from the authors' own consulting experience.
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Introduction to Data Science: Data Analysis and Algorithms with R
Introduces concepts and skills that can help tackling real-world data analysis challenges. Covers concepts from probability, statistical inference, linear regression, and machine learning. Helps developing skills such as R programming, data wrangling, etc.
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Regression Models for Data Science in R (Brian Caffo)
The book gives a rigorous treatment of the elementary concepts of regression models from a practical perspective. The ideal reader for this book will be quantitatively literate and has a basic understanding of statistical concepts and R programming.
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Geocomputation with R (Robin Lovelace, et al.)
This book is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities.
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