Multivariate Analysis (original) (raw)
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The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
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The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
A Practical Guide to the Use of Selected Multivariate Statistics Main Index
This document is set up to allow the user of multivariate statistics to get assistance in the choice of multivariate technique to use and the state the data must be in to use the desired technique. A series of links enable the user to view areas of interest in relation to multivariate statistical theory, use, and application.
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Recently statistical knowledge has become an important requirement and occupies a prominent position in the exercise of various professions. Every day the professionals use more sophisticated statistical tools to assist them in decision making. In the real world, the processes have a large volume of data and are naturally multivariate and as such, require a proper treatment. For these conditions it is difficult or practically impossible to use methods of univariate statistics. The wide application of multivariate techniques and the need to spread them more fully in the academic and the business justify the creation of this book. The objective is to demonstrate interdisciplinary applications to identify patterns, trends, associations and dependencies, in the areas of Management, Engineering and Sciences. The book is addressed to both practicing professionals and researchers in the field.
Journal of Multivariate Analysis
n. Such comparisons are called two-sample comparisons. It is shown that some of the results in this paper strengthen previous results in the literature. Some applications in reliability theory are described.
Multivariate and multidimensional analysis
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AN APPROACH FOR IMPROVED INTERPRETATION OF MULTIVARIATE ANALYSIS
Decision Sciences, 1978
This paper proposes a method, canonical rotation analysis, which facilitates the substantive interpretation of results in multivariate analysis. Canonical rotation analysis is developed as a model which integrates multivariate least squares approaches and the varimax rotation criterion. The generalized applicability of the model to canonical correlation, multiple discriminant analysis, and multivariate analysis of variance is developed. The advantages and limitations of canonical rotation analysis are discussed and illustrated in the context of an industrial marketing research problem.