The purpose of this book is to introduce multivariate statistical methods to non-mathematicians. It is not intended to be comprehensive. Rather, the intention is to keep the details to a minimum while still conveying a good idea of what can be done. In other words, it is a book to 'get you going' in a particular area of statistical methods. This second edition has retained all of Professor Manly's crystal clear style. It is based on a course that has been taught successfully at the University of Otago for a number of years but has increased coverage on measuring distances between cases based on presence-absence data, a new selection on logistic regression, new exercises and two completely new chapters on graphical methods and ordination. The author has taken into account the major shift in the way in which computer software is used, but the emphasis is on the underlying principles rather than the use of particular programs.
"synopsis" may belong to another edition of this title.
The previous edition (2E) was reviewed by Nemeth (1997), who was enthusiastic about the book's role as 'an excellent, easy-to-read introduction to the analysis of multivariate data'Her summary continues to work just fine for this new editionChapter summaries, always a nice feature, have been added throughoutthis is a nice book to have around to loan to people who are just getting started in multivariate analysis.
The statistical analysis of several related variables simultaneously, whilst sometimes not met with in introductory courses in statistics, is essential in a wide range of disciplines. The first edition of bryan Manly's little blue book has therefore become a vade mecum for students who have previously taken a standard introductory course of statistical methods. This new edition has retained all of Professor Manly's crystal clear style, based on a course that has been taught successfully at the University of Otago for a number of years. It has increased coverage on measuring distances between cases based on presence-absence data, a new section on logistic regression, new exercises and two completely new chapters on graphical methods and ordination. The author has taken into account the major shift in the way in which computer software is used. But of course its not how to run software that is important; it's an understanding of the underlying statistical principles which are crucial, which this book supplies with the simplest and most concise account. This book should be of interest to introductory courses in statistics for biologists and general scientists.
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