Beginning R: The Statistical Programming Language

Gardener, Mark

ISBN 10: 111816430X / ISBN 13: 9781118164303

Editore: Wrox, 2012

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Ships in a BOX from Central Missouri! Like Brand NEW. No tears, highlighting or writing because it's never been used! May have minor shelf wear. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Codice articolo 001357502N

Dati bibliografici

• Titolo: Beginning R: The Statistical Programming Language
• Editore: Wrox
• Data di pubblicazione: 2012
• Lingua: Inglese
• ISBN 10: 111816430X
• ISBN 13: 9781118164303
• Rilegatura: paperback
• Edizione: 1st Edition.
• Condizione: Like New

Descrizione articolo

Riassunto

Gain better insight into your data using the power of R

While R is very flexible and powerful, it is unlike most of the computer programs you have used. In order to unlock its full potential, this book delves into the language, making it accessible so you can tackle even the most complex of data analysis tasks. Simple data examples are integrated throughout so you can explore the capabilities and versatility of R. Along the way, you'll also learn how to carry out a range of commonly used statistical methods, including Analysis of Variance and Linear Regression. By the end, you'll be able to effectively and efficiently analyze your data and present the results.

Beginning R:

• Discusses how to implement some basic statistical methods such as the t-test, correlation, and tests of association

• Explains how to turn your graphs from merely adequate to simply stunning

• Provides you with the ability to define complex analytical situations

• Demonstrates ways to make and rearrange your data for easier analysis

• Covers how to carry out basic regression as well as complex model building and curvilinear regression

• Shows how to produce customized functions and simple scripts that can automate your workflow

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Informazioni sull?autore

Dr. Mark Gardener is an ecologist, lecturer, and writer working in the UK. He is currently self-employed and runs courses in ecology, data analysis, and R for a variety of organizations.