Book one:

R is an open-source statistical environment and programming language that has grown in popularity for data management and analysis in various industries. “R” Programming teaches you all the R you'll ever need in a rapid and painless manner.

This accessible tutorial taught you your way around a list with no previous programming expertise and loads of practical examples, step-by-step exercises, and sample code. This book covers the most significant modeling and prediction methods, as well as their applications.

Learn how to use R to transform raw data into knowledge, understanding, and insight. This book introduces you to R, RStudio, and the tidyverse, a set of R tools that work together to make data research simple, fluent, and enjoyable. This book is meant to get you practicing data science as fast as possible, even if you have no prior programming expertise. You'll get a comprehensive grasp of the data science cycle and the fundamental tools you'll need to handle the details.

R is becoming more well-known by the day, as large institutions embrace it as a standard. Its popularity stems partly from the fact that it is a free tool replacing expensive statistical software products that may take an undue amount of time to master. Furthermore, R allows a user to do complicated statistical analyses with only a few keystrokes, making advanced studies accessible and clear to a broad audience.

Learn how to import data, construct and dismantle data objects, traverse R's environment system, develop your own functions, and utilize all of R's programming tools with this book. This book will not only teach you how to program but also how to use R for more than simply displaying and analyzing data.

Most of the chapters are written for you to understand statistical data, so if you are a student, this book can guarantee to teach you some basic statistics that will help you get good grades.

The book is highly informative with lots of code. Following the book, you will be able to start Rstudio and use the program smoothly.

Book two:

Interested in statistical computing ?

R Programming: Data Analysis and Statistics is a beginner-friendly book. It is written in an accessible way, and deal with the basics as well as more complex problems.

No prior statistical knowledge is required.

This book may also help more advanced programmers expand their skills.

Book three:

This book is like a friend who advises and guides you on how to use the ggplot2 package for making data visualizations. With this book, you will learn how to get started with data visualization in R. You will learn basic concepts of graphics, and you will also learn how to perform statistical analyses.

This book is for everyone who faces a difficult task when trying to make data visualizations using R. It is also for people who are interested in learning more about statistics and graphical techniques.

The book also teaches listeners how to get started with ggplot2, and it also introduces the basics of R so that listeners are aware of the basic commands and functions in R, as well as importing libraries.

Think of R as a programming language that provides access to the power of machine learning and statistical computing. It's software used by statisticians and data scientists, with its capabilities in statistics, data visualization, machine learning, and more.