2020, Second Edition, updated version.
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Why Learn R? What are the reasons to learn R for Data Science? 

In this small textbook recommended for absolute beginners, the author tried to answer these types of questions. After reading this guide, maybe in one or two days, you will learn the basics of R programming and its utility for each Data Scientist. 

Indeed, R is a programming language and software environment for statistical analysis, graphics representation, and reporting. If you are trying to understand the R programming language as a beginner, this short book will give you enough understanding of almost all the concepts of the R language. The author will guide you through examples, how to program in R and how to use R for effective data analysis.
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[b]Book Objectives
[/b]

This book is about R programming. The following are the objectives of the author:

[*]To familiarize you with the basics of R programming language.
[*]To help you understand the various fields where R can be applied and its use cases in each field.
[*] To equip you with R programming skills, both beginner and advanced skills.
[*]To introduce you to R programming for data analysis.
[*]To introduce you to R programming for machine learning.
[*]To help you understand and appreciate the power of R in statistical computing, data analysis, and scientific research.

[b]Who this Book is for?
[/b]

[*]Anybody who is a complete beginner to R Programming.
[*] Anybody in need of advancing their R Programming skills.
[*] Professionals in computer programming.
[*]Professors, lecturers or tutors who are looking to find better ways to explain R programming to their students in the simplest and easiest way.
[*] Students and academicians, especially those focusing on R, Data Analysis,Machine Learning , computer science, and Databases development.

[b]Requirements
[/b]

The author expects you to have a computer installed with an operating system such as Linux, Windows or Mac OS X. 

[b]What is inside the book?
[/b]

[*]R BASICS
[*] R DATA TYPES
[*] R VARIABLES AND CONSTANTS
[*] R OPERATORS
[*] DECISION MAKING IN R
[*]R LOOPS
[*] R FUNCTIONS
[*]R CLASSES AND OBJECTS
[*] R FOR DATA SCIENCE
[*]R FOR MACHINE LEARNING

[b]From the Back Cover.
[/b]

R programming language is one of the most popular languages used by statisticians, data analysts, researchers to retrieve, clean, analyze, visualize and present data. This is a comprehensive book on how to get started with R programming, why you should learn it and how you can learn it. Daniel Bell begins by introducing the readers to the foundations of the R programming language. The aim is to help you understand, how the R interpreter works, the origin of the name R, how to set up the R programming environment, etc. The author has discussed the process of installing R on Windows, Linux and Mac OS. Moreover, the author has explored the basics of R programming including writing comments, using the R console, creating R script files, etc. 
The various features provided by R have been discussed in depth, including data types, variables, loops, decision making, functions, operators, classes, and objects, etc. The author has also discussed R for data science and R for machine learning. The book has been organized into chapters, with each chapter having many sub-chapters. R code scripts have been provided, alongside thorough explanations of the code and images showing the expected output upon the execution of every script. 

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