Using R for Statistics

Sarah Baldock

ISBN 10: 148420140X / ISBN 13: 9781484201404

Verlag: Apress, Apress Jun 2014, 2014

Beschreibung

Neuware -Using R for Statistics will get you the answers to most of the problems you are likely to encounter when using a variety of statistics. This book is a problem-solution primer for using R to set up your data, pose your problems and get answers using a wide array of statistical tests. The book walks you through R basics and how to use R to accomplish a wide variety statistical operations.You'll be able to navigate the R system, enter and import data, manipulate datasets, calculate summary statistics, create statistical plots and customize their appearance, perform hypothesis tests such as the t-tests and analyses of variance, and build regression models. Examples are built around actual datasets to simulate real-world solutions, and programming basics are explained to assist those who do not have a development background.After reading and using this guide, you'll be comfortable using and applying R to your specific statistical analyses or hypothesis tests. Noprior knowledge of R or of programming is assumed, though you should have some experience with statistics.APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 244 pp. Englisch.

Bestandsnummer des Verkäufers 9781484201404

Bibliografische Details

• Titel: Using R for Statistics
• Verlag: Apress, Apress Jun 2014
• Erscheinungsjahr: 2014
• Sprache: Englisch
• ISBN-10: 148420140X
• ISBN-13: 9781484201404
• Einband: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

Using R for Statistics will get you the answers to most of the problems you are likely to encounter when using a variety of statistics. This book is a problem-solution primer for using R to set up your data, pose your problems and get answers using a wide array of statistical tests. The book walks you through R basics and how to use R to accomplish a wide variety statistical operations.

You'll be able to navigate the R system, enter and import data, manipulate datasets, calculate summary statistics, create statistical plots and customize their appearance, perform hypothesis tests such as the t-tests and analyses of variance, and build regression models. Examples are built around actual datasets to simulate real-world solutions, and programming basics are explained to assist those who do not have a development background.

After reading and using this guide, you'll be comfortable using and applying R to your specific statistical analyses or hypothesis tests. No prior knowledge of R or of programming is assumed, though you should have some experience with statistics.

Über die Autorin bzw. den Autor

Sarah Stowell is a Contract Statistician with Mitsubishi Pharma Europe and has been a Statistician with MDSL International and GlaxoSmithKline previously. She holds a Master of Science degree in Statistics.