Goodreads helps you keep track of books you want to read.
Start by marking “Introductory Statistics with R (Statistics and Computing)” as Want to Read:
Introductory Statistics with R (Statistics and Computing)
Enlarge cover
Rate this book
Clear rating
Open Preview

Introductory Statistics with R (Statistics and Computing)

3.77  ·  Rating details ·  159 Ratings  ·  5 Reviews

R is an Open Source implementation of the S language. It works on multiple computing platforms and can be freely downloaded. R is now in widespread use for teaching at many levels as well as for practical data analysis and methodological development.

This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and s

...more
Paperback, 267 pages
Published February 10th 2004 by Springer (first published January 1st 2002)
More Details... edit details

Friend Reviews

To see what your friends thought of this book, please sign up.

Reader Q&A

To ask other readers questions about Introductory Statistics with R, please sign up.

Be the first to ask a question about Introductory Statistics with R

Community Reviews

(showing 1-30)
Rating details
Sort: Default
|
Filter
Jyotika Varmani
Apr 07, 2015 rated it really liked it
Though the book is very informative, I still found it to be at a difficulty level not suitable to the beginner. R is quite complicated anyway. The instructions to make use of it need to be put as simply as possible.

Nonetheless, the book is well organized, and detailed. A good textbook.
Julia Colleen
Nov 11, 2007 rated it really liked it
This is by far the best 'how-to-use-"R"' book... ever!
I highly recommend going through all of the exercises in the book. The data comes with the basic "R" download in the 'ISwR' library.
Terran M
Mar 21, 2018 rated it really liked it
If you already understand the concepts of frequentist statistics, this book will clearly show you how to apply them using R, and get you from zero to a place where you can comfortably learn more from the online documentation. The book is clearly written and has copious examples; the explanations of the meaning of the output is often better than the library documentation. The chapter on manipulating data in R is particularly strong with both clear exposition and a good selection of what to cover ...more
Yuta Tamberg
Apr 29, 2011 rated it liked it
Not only a good starting point, but also pretty useful handbook
Mike
Sep 26, 2007 rated it liked it
Nothin' but love for R.
Bruce Lowther
rated it liked it
Jun 01, 2014
Danielle Romain
rated it liked it
Jun 11, 2014
Kevin Gomez
rated it really liked it
Nov 20, 2014
Derek Norton
rated it liked it
Sep 16, 2014
Luis
rated it really liked it
Oct 21, 2012
Shane Emmons
rated it really liked it
Sep 01, 2014
Alan  Eister
rated it it was amazing
Jan 01, 2017
John Hunter
rated it really liked it
Feb 26, 2014
Sarah
rated it it was amazing
Oct 11, 2014
Justin
rated it liked it
Aug 18, 2016
Wei-ling
rated it it was ok
Aug 01, 2014
Jeremy
rated it liked it
Sep 11, 2015
Charbel Mrad
rated it it was amazing
Jan 16, 2017
Andy Yeh
rated it liked it
Dec 05, 2010
Chris McNeilly
rated it really liked it
Nov 17, 2014
Lyndon
rated it liked it
Sep 01, 2014
Roger
rated it it was amazing
Sep 19, 2017
Mirza Avman Ahmed
rated it really liked it
May 02, 2016
Kristina Weber
rated it really liked it
Feb 05, 2018
Jonathan Brier
rated it liked it
May 27, 2015
Mae Coughlin
rated it liked it
Sep 30, 2014
Russ
rated it liked it
Jan 01, 2016
Jason
rated it liked it
Sep 30, 2014
Mncockerham
rated it really liked it
Feb 04, 2015
Jill Card
rated it it was amazing
Aug 17, 2015
« previous 1 3 4 5 6 next »
There are no discussion topics on this book yet. Be the first to start one »
  • R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics
  • Statistical Inference
  • Bayesian Data Analysis
  • The Art of R Programming: A Tour of Statistical Software Design
  • Mathematical Statistics and Data Analysis
  • Linear Algebra
  • Multivariable Calculus
  • Numerical Analysis
  • R in a Nutshell: A Desktop Quick Reference
  • R Graphics Cookbook
  • Algorithms
  • The Elements of Statistical Learning: Data Mining, Inference, and Prediction
  • All of Statistics: A Concise Course in Statistical Inference
  • Pattern Recognition and Machine Learning
  • Data Mining With R: Learning By Case Studies
  • Linear Algebra Done Right
  • Elementary Analysis: The Theory of Calculus
  • Food: Your Miracle Medicine

Goodreads is hiring!

If you like books and love to build cool products, we may be looking for you.
Learn more »