Discovering Statistics Using R Author: Andy Field Jeremy Miles Zoe Field | Language: English | ISBN:
B00HPZ4VVM | Format: PDF
Discovering Statistics Using R Description
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Watch Andy Field's introductory video to Discovering Statistics Using R
Keeping the uniquely humorous and self-deprecating 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 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 you discover the importance of exploring and graphing data, before moving onto statistical tests that are the foundations of the rest of the book (for example correlation and regression). You will then stride confidently into intermediate level analyses such as ANOVA, before ending your journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help you gain the necessary conceptual understanding of what you're doing, the emphasis is on applying what you learn to playful and real-world examples that should make the experience more fun than you might expect.
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, together with hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more at: Instructor Site.
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.
- File Size: 23478 KB
- Print Length: 992 pages
- Page Numbers Source ISBN: 1446200469
- Publisher: SAGE Publications (December 19, 2013)
- Sold by: Amazon Digital Services, Inc.
- Language: English
- ASIN: B00HPZ4VVM
- Text-to-Speech: Enabled
X-Ray:
- Lending: Not Enabled
- Amazon Best Sellers Rank: #74,576 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
- #10
in Kindle Store > Kindle eBooks > Education & Reference > Writing, Research & Publishing Guides > Research - #31
in Kindle Store > Kindle eBooks > Nonfiction > Science > Mathematics > Applied > Probability & Statistics - #31
in Kindle Store > Kindle eBooks > Nonfiction > Professional & Technical > Professional Science > Mathematics > Applied > Statistics
- #10
in Kindle Store > Kindle eBooks > Education & Reference > Writing, Research & Publishing Guides > Research - #31
in Kindle Store > Kindle eBooks > Nonfiction > Science > Mathematics > Applied > Probability & Statistics - #31
in Kindle Store > Kindle eBooks > Nonfiction > Professional & Technical > Professional Science > Mathematics > Applied > Statistics
Being familiar with the author's SPSS book and wanting to learn R, I leapt at the chance to purchase this book. As I write this, I've been able to go through all the chapters save the last two. The book is a great overview of statistics concepts and provides a gentle, yet comprehensive, introduction to the R language. I'm extremely pleased I bought it.
The author's writing style is conversational and humorous, and some of his examples are outrageous (I didn't know whether to laugh or cry during the logistic regression chapter!). I think this would make the material more accessible to students who are ambivalent about statistics and R. However, though the material is presented in an easy-going manner, it is nevertheless quite comprehensive. The essence of each statistical method is discussed thoroughly, and the procedures for doing these tests in R are clearly detailed in a step by step manner.
What I liked most about the book were the problems at the end of each chapter and the detailed solutions to those problems on the book's accompanying website. I found these excellent for self-study.
To be clear, the book is not the most technical treatise on either statistics or R. The book gives a good overview of the concepts of each statistical method, but computation is kept to a minimum. Similarly, while the book describes how to create functions in R and has several challenging examples, you will only scratch the surface of what R can do. It seems intended primarily for non-mathematics undergraduate students who aspire to doing research in their fields. However, for someone like me who wanted a context in which to become familiar with R, it is invaluable.
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