An entertaining exploration of aspects of chance, risk and probability, ranging from the toss of a coin to the use of clinical trials in medicine and the evaluation of alternative therapies. Aimed at all those who would like to discover more about chance and the way it operates in a variety of settings, the book is written by the prolific author, Professor Brian S. Everitt, Head of the Biostatistics and Computing Department at Kings College, London.

Chance Rules: An Informal Guide to Probability, Risk and Statistics

Science & Math

Brian S. Everitt

Mathematics

Springer

For several years now my book Analysing Qualitative Data has been in need of revision. Since it was first published in 1961, and in part perhaps because of it, a great deal of new and interesting work on the analysis of contingency tables has been published. Mr. Brian Everitt kindly undertook to do the revision but, when he came to review recent literature, it became apparent that a mere renovation of the original text would not be enough; the amount of new work was not only extensive but also made obsolete many of the older methods. In consequence, and with the agreement of the publishers, it was decided that the revised version should in effect be a new book. That it is so is not strikingly evident in the first two chapters of the present text which, by way of introduction, cover old ground. Thereafter, the increased scope of new methods becomes abundantly apparent. This can be illustrated by a single example. When the Iiterature up to 1961 was reviewed the big disappointment was the paucity and inadequacy of methods then available for the analysis of multidimensional tables, and they are the rule rather than the exception in research work in the social sciences.

The Analysis of Contingency Tables (Monographs on Statistics and Applied Probability)

Computers & Technology

Computer Science

Chapman & Hall

Cluster analysis (Reviews of current research ; 11)

This practical text has been reworked to provide an account of the subject of cluster analysis - the generic name for a wide variety of procedures involved with identifying groups within data. By organizing multivariate data into such subgroups clustering may help the investigator discover the characteristics of any structure or pattern present. However, applying the methods in practice requires considerable care and researchers may need guidance in order to avoid misinterpreting results. It offers an applied approach using limited mathematics, contains detailed descriptions of recent methods along with numerous examples and includes information on the software packages available. Other titles by Brian S. Everitt include "Talking About Statistics: A Psychologist's Guide to Design and Analysis" (with Dale F. Hay), "Applied Multivariate Data Analysis" (with Graham Dunn) and "Statistical Methods for Medical Investigations".

Heinemann Educational Publishe

Encyclopedia Of Statistics In Behavioral Science

David Howell

Wiley & Sons, Incorporated, John

A Handbook of Statistical Analyses Using R

Torsten Hothorn

CRC-Press

A Handbook of Statistical Analyses using R

Chapman and Hall/CRC

R is dynamic, to say the least. More precisely, it is organic, with new functionality and add-on packages appearing constantly. And because of its open-source nature and free availability, R is quickly becoming the software of choice for statistical analysis in a variety of fields. Doing for R what Everitt's other Handbooks have done for S-PLUS, STATA, SPSS, and SAS, A Handbook of Statistical Analyses Using R presents straightforward, self-contained descriptions of how to perform a variety of statistical analyses in the R environment. From simple inference to recursive partitioning and cluster analysis, eminent experts Everitt and Hothorn lead you methodically through the steps, commands, and interpretation of the results, addressing theory and statistical background only when useful or necessary. They begin with an introduction to R, discussing the syntax, general operators, and basic data manipulation while summarizing the most important features. Numerous figures highlight R's strong graphical capabilities and exercises at the end of each chapter reinforce the techniques and concepts presented. All data sets and code used in the book are available as a downloadable package from CRAN, the R online archive. A Handbook of Statistical Analyses Using R is the perfect guide for newcomers as well as seasoned users of R who want concrete, step-by-step guidance on how to use the software easily and effectively for nearly any statistical analysis.

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Books by Brian S. Everitt