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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