Download Instant R: An Introduction to R for Statistical Analysis, by Sarah Stowell
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Instant R: An Introduction to R for Statistical Analysis, by Sarah Stowell
Download Instant R: An Introduction to R for Statistical Analysis, by Sarah Stowell
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The R software is rapidly growing in popularity as a statistical analysis package due to its versatility, attractive graphics and open source license.
This book gives an introduction to using R, with a focus on performing popular statistical methods. It is suitable for anyone that is familiar with basic statistics and wants to begin using R to analyse data and create statistical plots.
No prior knowledge of R or of programming is assumed, making this book ideal if you are more accustomed to using point-and-click style statistical packages.
You will learn how to:�
- Navigate the R system
- Enter and import data
- Manipulate datasets
- Calculate summary statistics
- Create statistical plots and customise their appearance
- Perform hypothesis tests such as the t-test and analysis of variance
- Build regression models
- Create your own functions
- Access additional functionality with the use of add-on packages.
- Sales Rank: #2432365 in Books
- Published on: 2013-01-04
- Released on: 2013-01-04
- Original language: English
- Dimensions: 9.68" h x .49" w x 7.44" l,
- Binding: Paperback
- 214 pages
Most helpful customer reviews
0 of 0 people found the following review helpful.
Best basic introduction to R
By Dr. R. E. Wyllys
I've acquired quite a few introductions to, and expositions of, R. Among them all, I consider Sarah Stowell's "Instant R" to be the best introduction to R for the general reader or student. Individual steps are laid out and explained in an unusually helpful fashion.
The book begins by covering basic descriptive statistics, including a variety of plots. It goes on to cover the basic statistical tests treated in the usual first semester course in inferential statistics: e.g., Pearson and Spearman correlation, t-tests, ANOVA, rank-sum tests, linear and multiple regression, chi-square goodness-of-fit test, chi-square test of association, and the Kolmogorov-Smirnov test.
I even gave a copy of this book to a young single mother whom my wife and I know and admire because she works full time while simultaneously being a part-time student pursuing her Registered Nurse certification. This woman has also found Stowell's book to be a very helpful introduction to R, and feels that it has helped her earn her grade of "A" as of mid-semester in her statistics course.
2 of 3 people found the following review helpful.
Clear and detailed
By Charles Sanders
I purchased this book as a supplement to a population modeling course that uses R extensively. I was happy to see that it assumes the reader has no experience in using R whatsoever, and is as clear as possible about how to enter code. They do assume some minor knowledge in writing script, and some basic computer programming experience (even just HTML) is useful. The book is laid out in a format that resembles some of my automotive textbooks from a vocational program at community college, and as a result is easy to follow. I like the lists of commands at the end of the chapters, and have referred to those often.
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