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Discovering Statistics Using R



The book is written by Andy Field and Jeremy Miles and is about teaching statistics in R. It is aimed at people who have no prior experience in statistics and is written in a humorous and self-depreciating style. The book starts with explaining basic statistical concepts and then moves on to exploring data with graphs and statistical tests. It then goes on to intermediate level analyses such as AN... more details
Key Features:
  • Written by Andy Field and Jeremy Miles
  • Aimed at people with no prior experience in statistics
  • Written in a humorous and self-depreciating style


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Features
Author andy field
Format paperback
ISBN 9781446200469
Manufacturer Unbranded
Model Number 9781446200469
Pages 957
Description
The book is written by Andy Field and Jeremy Miles and is about teaching statistics in R. It is aimed at people who have no prior experience in statistics and is written in a humorous and self-depreciating style. The book starts with explaining basic statistical concepts and then moves on to exploring data with graphs and statistical tests. It then goes on to intermediate level analyses such as ANOVA and moves on to more advanced techniques such as MANOVA and multilevel models. The book is written in an accessible and fun style and is the course text for all statistics classes at the author's university.

Hot on the heals of the award-winning and best selling Discovering Statistics Using SPSS, Third Edition, Andy Field has teamed up with Jeremy Miles (co-author of Discovering Statistics Using SAS) to write Discovering Statistics Using R. Keeping the uniquely humorous and self-depreciating style that has made students across the world fall in love with Andy Field's books, Discovering Statistics Using R takes students on a journey of statistical discovery using the freeware R, a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences throughout the world. The journey begins by explaining basic statistical and research concepts before a guided tour of the R software environment. Next the importance of exploring and graphing data will be discovered, before moving onto statistical tests that are the foundations of the rest of the book (for e.g. correlation and regression). Readers will then stride confidently into intermediate level analyses such as ANOVA, before ending their journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help the reader gain the necessary conceptual understanding of what they're doing, the emphasis is on applying what's learned to playful and real-world examples that should make the experience more fun than expected. Like its sister textbooks, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is augmented by a cast of characters to help the reader on their way, hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more (at www.sagepub.co.uk/fieldandmilesR). Given this book's accessibility, fun spirit, and use of bizarre real-world research it should be essential for anyone wanting to learn about statistics using the freely-available R software.
Review:
In statistics, R is the way of the future. The big boys and girls have known this for some time: There are now millions of R users in academia and industry. R is free (as in no cost) and free (as in speech). Andy, Jeremy, and Zoe's book now makes R accessible to the little boys and girls like me and my students. Soon all classes in statistics will be taught in R. I have been teaching R to psychologists for several years and so I have been waiting for this book for some time. The book is excellent, and it is now the course text for all my statistics classes. I'm pretty sure the book provides all you need to go from statistical novice to working researcher. Take, for example, the chapter on t-tests. The chapter explains how to compare the means of two groups from scratch. It explains the logic behind the tests, it explains how to do the tests in R with a complete worked example, which papers to read in the unlikely event you do need to go further, and it explains what you need to write in your practical report or paper. But it also goes further, and explains how t-tests and regression are related---and are really the same thing---as part of the general linear model. So this book offers not just the step-by-step guidance needed to complete a particular test, but it also offers the chance to reach the zen state of total statistical understanding. Prof. Neil Stewart Warwick University Field's Discovering Statistics is popular with students for making a sometimes deemed inaccessible topic accessible, in a fun way. In Discovering Statistics Using R, the authors have managed to do this using a statistics package that is known to be powerful, but sometimes deemed just as inaccessible to the uninitiated, all the while staying true to Field's off-kilter approach. Dr Marcel van Egmond University of Amsterdam Probably the wittiest and most amusing of the lot (no, really), this book takes yet another approach: it is 958 pages of R-based stats wisdom (plus online accoutrements)... A thoroughly engaging, expansive, thoughtful and complete guide
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