| Author: | Michael J. Crawley | ISBN: | 9781118941102 |
| Publisher: | Wiley | Publication: | September 23, 2014 |
| Imprint: | Wiley | Language: | English |
| Author: | Michael J. Crawley |
| ISBN: | 9781118941102 |
| Publisher: | Wiley |
| Publication: | September 23, 2014 |
| Imprint: | Wiley |
| Language: | English |
"...I know of no better book of its kind..." (Journal of the Royal Statistical Society, Vol 169 (1), January 2006)
A revised and updated edition of this bestselling introductory textbook to statistical analysis using the leading free software package R
This new edition of a bestselling title offers a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a wide range of disciplines. Step-by-step instructions help the non-statistician to fully understand the methodology. The book covers the full range of statistical techniques likely to be needed 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.
"...I know of no better book of its kind..." (Journal of the Royal Statistical Society, Vol 169 (1), January 2006)
A revised and updated edition of this bestselling introductory textbook to statistical analysis using the leading free software package R
This new edition of a bestselling title offers a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a wide range of disciplines. Step-by-step instructions help the non-statistician to fully understand the methodology. The book covers the full range of statistical techniques likely to be needed 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.
