This first volume of a two part work on multivariate analysis concentrates on what might be termed the 'basic' techniques: topics covered range from initial inspection and graphical display of multivariate data through informal data-based methods such as principal components, canonical variates and multi-dimensional scaling, to inferential procedures such as two-sample hypothesis tests and the multivariate general linear model. The latter procedures are based on the multivariate normal distribution, so a comprehensive chapter on distribution theory lays the necessary foundations. Whilst full technical details are supplied, the emphasis throughout is on providing a readble and 'user-friendly' presentation.
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A common and important statistical technique, multivariate analysis has applications in a wide range of fields of study including subjects as diverse as biology and linguistics. This two part overview provides comprehensive coverage of all the available techniques for analyzing data in this form. The first part, on distributions, ordination and inference, concentrates on basic techniques. While full technical details are supplied, the emphasis throughout is on a readable and user-friendly presentation with ample use of illustrative exercises.
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