| Title: | Introductory Statistics with R |
| Other Titles: | Statistics and Computing |
| Authors: | Dalgaard, Peter |
| Keywords: | Statistics Computing |
| Issue Date: | 2008 |
| Publisher: | Springer |
| Abstract: | R is a statistical computer program made available through the Internet under the General Public License (GPL). That is, it is supplied with a li- cense that allows you to use it freely, distribute it, or even sell it, as long as the receiver has the same rights and the source code is freely available. It exists for Microsoft Windows XP or later, for a variety of Unix and Linux platforms, and for Apple Macintosh OS X. R provides an environment in which you can perform statistical analysis and produce graphics. It is actually a complete programming language, although that is only marginally described in this book. Here we content ourselves with learning the elementary concepts and seeing a number of cookbook examples. R is designed in such a way that it is always possible to do further computations on the results of a statistical procedure. Furthermore, the design for graphical presentation of data allows both no-nonsense meth- ods, for example plot(x,y), and the possibility of fine-grained control of the output’s appearance. The fact that R is based on a formal computer language gives it tremendous flexibility. Other systems present simpler interfaces in terms of menus and forms, but often the apparent user- friendliness turns into a hindrance in the longer run. Although elementary statistics is often presented as a collection of fixed procedures, analysis of moderately complex data requires ad hoc statistical model building, which makes the added flexibility of R highly desirable. |
| Description: | This book is not a manual for R. The idea is to introduce a number of basic concepts and techniques that should allow the reader to get started with practical statistics. In terms of the practical methods, the book covers a reasonable curriculum for first-year students of theoretical statistics as well as for engineering students. These groups will eventually need to go further and study more complex models as well as general techniques involving actual programming in the R language. For fields where elementary statistics is taught mainly as a tool, the book goes somewhat further than what is commonly taught at the under- graduate level. Multiple regression methods or analysis of multifactorial experiments are rarely taught at that level but may quickly become essen- tial for practical research. I have collected the simpler methods near the beginning to make the book readable also at the elementary level. How- ever, in order to keep technical material together, Chapters 1 and 2 do include material that some readers will want to skip. The book is thus intended to be useful for several groups, but I will not pretend that it can stand alone for any of them. I have included brief theoretical sections in connection with the various methods, but more than as teaching material, these should serve as reminders or perhaps as appetizers for readers who are new to the world of statistics. |
| URI: | http://localhost:8080/xmlui/handle/123456789/65 |
| ISBN: | 978-0-387-79054-1 |
| Appears in Collections: | ARTS & SCIENCE |
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2008_Book_IntroductoryStatisticsWithR.pdf | 2.97 MB | Adobe PDF | View/Open |
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