Bøger af Brian S. Everitt

Most data sets collected by researchers are multivariate, and in the majority of cases the variables need to be examined simultaneously to get the most informative results. This requires the use of one or other of the many methods of multivariate analysis, and the use of a suitable software package such as S-PLUS or R.In this book the core multivariate methodology is covered along with some basic theory for each method described. The necessary R and S-PLUS code is given for each analysis in the book, with any differences between the two highlighted. Graduate students, and advanced undergraduates on applied statistics courses, especially those in the social sciences, will find this book invaluable in their work, and it will also be useful to researchers outside of statistics who need to deal with the complexities of multivariate data in their work. From the reviews:"This text is much more than just an R/S programming guide. Brian Everitt's expertise in multivariate data analysis shines through brilliantly." Journal of the American Statistical Association, June 2006

During the last twenty years statistical methodology has become of central importance in research studies in medicine and also in day-to-day clinical practice.

Deals with the analysis of contingency table data arising from observations on two or more qualitative variables. This second edition offers expanded coverage of methods which have developed over the last decade and includes an account of correspondence analysis.

The main message of this book is that people should be on their guard against both scare stories about risks to health, and claims for miracle cures of medical conditions.

Almost all undergraduate psychology students are exposed to an introductory statistics course during their first year of study. In their second and third years (and possibly in later postgraduate courses), many psychology students are encouraged to learn

* Presents a comprehensive guide to clustering techniques. * Provides a thorough revision of the fourth edition, including new developments in clustering longitudinal data and examples from bioinformatics and gene studies * Includes a new section on how to use R for cluster analysis.

Almost all undergraduate psychology students are exposed to an introductory statistics course during their first year of study. In their second and third years (and possibly in later postgraduate courses), many psychology students are encouraged to learn

Demonstrates how a wide variety of statistical analyses, including descriptive statistics, graphics, and model estimation and diagnostics, can be performed using Stata version 9. This book presents many of Stata's features, including a mixed-models estimation command and a matrix language.

Applied statisticians often need to perform analyses of multivariate data; This book sets out how to use these packages for these analyses in a concise and easy-to-use way, and will save users having to buy two books for the job. The author is well-known for this kind of book, and so buyers will trust that he's got it right.