This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. Key Features: Provides a comprehensive, practical and accessible introduction to multivariate analysis. Keeps mathematical details to a minimum, so particularly geared toward a non-statistical audience. Includes lots of detailed worked examples, guidance on computing, and exercises. Updated with a new chapter on data visualization.

This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. Key Features: Provides a comprehensive, practical and accessible introduction to multivariate analysis. Keeps mathematical details to a minimum, so particularly geared toward a non-statistical audience. Includes lots of detailed worked examples, guidance on computing, and exercises. Updated with a new chapter on data visualization.

"Clear and concise in its recommendations, this book should find its place on lists of required reading for all practical survey design and analysis courses." --The Statistician Although data processing is frequently thought to occur only after the data are collected, it actually occurs throughout the phase of study design, implementation, and analysis. Decisions made during the design of data collection instrument influence the kind of data and the format of the data available for analysis. Devoted entirely to data processing, this much needed volume addresses such key issues as: Should you create your own instrument for a questionnaire? How do you test a questionnaire? What are the characteristics of good data processing? How do you deal with missing data? How do you scale an evaluation and create subfiles for analysis? Processing Data begins with a discussion on the selection of the data selection techniques and how this impacts data processing and the data for later analysis. Each major section concludes with examples, and when appropriate, directs the reader to commonly available computer software that can aid in data processing.