Experts Tell Us the Best Books To Learn R

This book essentially focuses on the 20% of R functionality that one needs to accomplish 80% of modern data tasks by effectively providing readers with extensive hands-on practice as well as sample code. The first 13 chapters encapsulate the basics of the R language, so if you are new to R, then you are bound to find them extremely useful. Meanwhile, the remaining chapters cover statistical learning techniques, so you don’t even need any prior programming experience to pick up this book.

In a world where we cannot predict what will happen tomorrow, the best we can do is to set ourselves, our children, our friends and our companies up to create conditions that make the best out of whatever might happen. This wise, exciting, and life-changing book suggests that we do not have to have it all figured out, but that a serendipity mindset enables us to navigate the future. It includes inspiring stories and practical recommendations based on a scientific framework for cultivating serendipity (smart luck) in our lives.

R for Data Science is a book written by Hadley Wickham (Author), Garrett Grolemund. The book guides you through the steps of importing, exploring, and modeling your data. This reference material also provides a complete, big-picture understanding of the data science cycle. You will also learn the basic tools you need to manage the details of R implementation. Each section included in this book is paired with exercises to help you practice what you’ve learned along the way.

Dalgaard P (2004) Introductory Statistics with R: this book is especially good for those starting to learn not only R, but statistics in general.

J Maindonald, JW Braun (2010) Data Analysis and Graphics Using R: An Example-based Approach: a somewhat more complexly written book that nevertheless gives a broad overview of statistical methods implemented with R, and has many examples.