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- Title: Advanced R Course
- Author(s): Florian Prive
- Publisher: GitHub (Continuously updating. Last updated on 2023-08-22)
- License(s): CC BY-SA 3.0
- Paperback: N/A
- eBook: HTML
- Language: English
- ISBN-10: N/A
- ISBN-13: N/A
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It is impossible to become expert in R in only one training course. Yet, this course aims at giving a wide understanding of many aspects of R. Some external resources will be referred to in this book for you to be able to deepen what you would have learned in this course.
It is for working professionals, researchers, or students who are familiar with R and basic statistical techniques such as linear regression and who want to learn how to take their R coding and programming to the next level.
Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R's functionality.
- How to access R’s thousands of functions, libraries, and data sets
- How to draw valid and useful conclusions from your data
- How to create publication-quality graphics of your results
- Florian Privé is a PhD student in predictive human genetics, fond of Data Science and an R(cpp) enthusiast. He is also the founder and co-organizer of the Grenoble R user group.
- The R Programming Language
- Statistics, and SAS Programming
- Data Analysis and Data Mining
- Data Science
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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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Efficient R Programming: Practical Guide to Smarter Programming
This book is about increasing the amount of work you can do with R in a given amount of time. It's about both computational and programmer efficiency. This book is for anyone who wants to make their use of R more reproducible, scalable, and faster.
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Cookbook for R: Best R Programming TIPs (Winston Chang)
The goal of this cookbook is to provide solutions to common tasks and problems in analyzing data. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works.
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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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