ISBN 9788126541201,Beginning R : The Statistical Programming Language

Beginning R : The Statistical Programming Language


Mark Gardener



Wiley India Pvt Ltd

Publication Year 2008

ISBN 9788126541201

ISBN-10 8126541202


Number of Pages 700 Pages
Language (English)

Computer software

This book is about data analysis and the programming language called R. This is rapidly becoming the de-facto standard amongst professionals and is used in every conceivable discipline from science and medicine to business and engineering. This book delves into the language of R and makes it accessible using simple data examples to explore its power and versatility. In learning how to "speak R" you will unlock its potential and gain better insights into tackling even the most complex of data analysis tasks. Salient Features This book will be light enough to appeal to beginning users, yet robust enough for a seasoned user to learn from it because it: Appeals to programmers wanting to narrow the skills gap (McKinsey Consulting states nearly 200,000 people will be needed with R knowledge in the US alone). Guides the reader in cutting cost in whatever industry they work in. Teaches the basics of the R language rather than just recipes by providing simple data examples that allow users to see what is happening while permitting complex analysis. It can be used as a complete reference to perform simple to complex tasks in R. About the Author Dr. Mark Gardener is an ecologist and lecturer as well as a teacher for the Open University (Environmental) science. He teaches biometrics and using R for conservation bodies, individuals and governmental agencies. His real world experience gives him good insight into what users require in learning R. Was this product information helpful? Yes No TABLE OF CONTENTS Introduction Chapter 1: Introducing R: What It Is and How to Get It Chapter 2: Starting Out: Becoming Familiar with R Chapter 3: Starting Out: Working with Objects Chapter 4: Data: Descriptive Statistics and Tabulation Chapter 5: Data: Distribution Chapter 6: Simple Hypothesis Testing Chapter 7: Introduction to Graphical Analysis Chapter 8: Formula Notation and Complex Statistic s Chapter 9: Manipulating Data and Extracting Components Chapter 10: Regression (Linear Modeling) Chapter 11: More about Graphs Chapter 12: Writing Your Own Scripts: Beginning to Program Summary Appendix: Answers to Exercise