Introduction to R Programming: Invent the Future

Learn to make sense of complex amounts of data through machine learning, data analysis and visualization with the R programming language. R is increasingly becoming the language of choice by major data companies and research institutions?

Are you looking for a comprehensive guide that will break down the seemingly complex subject using a language that you can easily follow, complete with examples to help you follow every step of the learning process?

If you’ve answered YES,

This Book Will Introduce You To The World Of R Programming And Hold You By The Hand Until You Are Confident About Your Ability To Leverage The Power Of Its Many Capabilities To Your Advantage!

R is one of the world’s most popular programming languages for statistical analysis. However, many programmers still complain a lot about R and this is understandable – R language can be frustrating to deal with at times while trying to master its data analysis features.

Luckily, we can tame this curve by putting aside visualization and focus on working with the data. This is where R shines. Analysts and Developers are becoming more aware of R everyday as major institutions are adopting it as a standard. Part of its appeal is that it is a free tool that’s taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn.

That’s not all; R, unlike other software packages, can carry out complex statistical analyses by entering a few commands, making sophisticated analyses available understandable to its audience.

Truth be told R language is the way to go in analyzing statistical data.

But perhaps you’re wondering…

Why do we need to use R – are there no other tools that are equally good for the job?

Who uses R anyway?

How do you install packages in R to get them up and running?

How is R used for predictive analysis?

Does version in R really matter?

How do you make the most of the many functionalities that R offers?

If you have these and other related questions, this book provides a comprehensive and easy to understand explanation of the R language.

More precisely, you will discover:

• Exactly how you can download and install and starting working with R, with few examples to draw valid conclusions from your data and R’s useful functions
• How to manage R, the foundation of R and the practice basics used in applying expressions and vectors
• Detailed information on practice control structures, R data structures, practical data structures and how to deal with functions
• How to read external data, custom formatted data, OOP and aims to practice OOP
• How to use R to bring statistical concepts like probability distributions, simple linear regression, statistical tests to life to make sense of both simple and complex data
• And so much more!

Even if you have little or no programming experience, with this book, you’ll find everything you need to know about R for statistical analysis.

So, what are you waiting for?!