Items related to Statistics: An Introduction using R
Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing.
* Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology.
* Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data.
* The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing.
* Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling.
* Includes numerous worked examples and exercises within each chapter.
* Accompanied by a website featuring worked examples, data sets, exercises and solutions:
http://www.imperial.ac.uk/bio/research/crawley/statistics
Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology - but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.
* Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology.
* Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data.
* The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing.
* Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling.
* Includes numerous worked examples and exercises within each chapter.
* Accompanied by a website featuring worked examples, data sets, exercises and solutions:
http://www.imperial.ac.uk/bio/research/crawley/statistics
Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology - but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.
"synopsis" may belong to another edition of this title.
Review:
"...the book contains some very good concepts..." (The American Statistician, February 2007)
"...will provide you with enhanced statistical insights...and access to a free and powerful computing language." (Clinical Chemistry, May 2006)
"...I know of no better book of its kind..." (Journal of the Royal Statistical Society, Vol 169 (1), January 2006)
"...offers a demanding, non-calculus-based coverage of such standard topics as hypothesis testing, modeling, regression, ANOVA, and count data." (CHOICE, November 2005)
"Appeal[s] to a broad range of disciplines" (Zentralblatt MATH Volume 1080)
"About this title" may belong to another edition of this title.
- PublisherWiley
- Publication date2005
- ISBN 10 0470022973
- ISBN 13 9780470022979
- BindingHardcover
- Edition number1
- Number of pages342
- Rating
Top Search Results from the AbeBooks Marketplace
Stock Image
Statistics: An Introduction using R
Seller:
Rating
Book Description Condition: Good. [ No Hassle 30 Day Returns ][ Ships Daily ] [ Underlining/Highlighting: NONE ] [ Writing: NONE ] [ Edition: first ] Publisher: John Wiley & Sons Pub Date: 5/13/2005 Binding: Hardcover Pages: 304 first edition. Seller Inventory # 6424610
Buy Used
US$ 1.16
Convert currency
Stock Image
Statistics: An Introduction using R
Seller:
Rating
Book Description Condition: Good. SHIPS FROM USA. Used books have different signs of use and do not include supplemental materials such as CDs, Dvds, Access Codes, charts or any other extra material. All used books might have various degrees of writing, highliting and wear and tear and possibly be an ex-library with the usual stickers and stamps. Dust Jackets are not guaranteed and when still present, they will have various degrees of tear and damage. All images are Stock Photos, not of the actual item. book. Seller Inventory # 15-0470022973-G
Buy Used
US$ 15.97
Convert currency