Statistical Analysis with R
Beginner's Guide
By John M. Quick
Publisher: Packt Publishing
Final Release Date: October 2010
Pages: 300

In Detail

R is a data analysis tool, graphical environment, and programming language. Without any prior experience in programming or statistical software, this book will help you quickly become a knowledgeable user of R. Now is the time to take control of your data and start producing superior statistical analysis with R.

This book will take you on a journey as the strategist for an ancient Chinese kingdom. Along the way, you will learn how to use R to arrive at practical solutions and how to effectively communicate your results. Ultimately, the fate of the kingdom depends on your ability to make informed, data-driven decisions with R.

You have unexpectedly been thrust into the role of lead strategist for the kingdom. After you install your predecessor's mysterious data analysis tool, you will begin to explore its fundamental elements. Next, you will use R to import and organize your data. Then, you will use functions and statistical analysis to arrive at potential courses of action. Subsequently, you will design your own functions to assess the practical impacts of your predictions. Lastly, you will focus on communicating your results through the use of charts, plots, graphs, and custom built visualizations. The fate of the kingdom is in your hands. Your rapid development as a master R strategist is the key to future success.

A step by step guide to organize, analyze, and visualize your data in R.


This is a practical, step by step guide that will help you to quickly become proficient in the data analysis using R. The book is packed with clear examples, screenshots, and code to carry on your data analysis without any hurdle.

Who this book is for

If you are a data analyst, business or information technology professional, student, educator, researcher, or anyone else who wants to learn to analyze the data effectively then this book is for you.

No prior experience with R is necessary. Knowledge of other programming languages, software packages, or statistics may be helpful, but is not required.

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