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Approach of the Book: Primary emphasis is on statistical methodology as applied to various scientic disciplines. SAS software is used as the crucial computational aid to carry out various intensive calcu- lations which so naturally occur in any typical multivariate analysis application. Discussion in this volume is limited to only the normal theory-based multivariate analysis. We believe that those who use multivariate methods should not only understand appro- priate statistical techniques useful in their particular situation but should also be able to discern the appropriate approach and distinguish it from an approach that seems correct but is completely inappropriate in a particular context. Quite often, these differences are subtle, and there are scenarios where the presumably best approach may be completely invalid due to one reason or the other. The problem is further compounded by the under- standable temptation to take the shortest route by choosing the analysis that can be readily performed using a particular software package or a canned computer program, regardless of its appropriateness, over a more appropriate analysis not so readily available. This book attempts to demonstrate this process of discernment, problem denition, selection of an appropriate analysis or a combination of many, while providing both the needed SAS code to achieve these goals and the subsequent interpretation of the SAS output. This approach largely eliminates the need for two books, one for learning multivariate techniques and another for mastering the software usage. Instead of taking various multi- variate procedures in SAS one at a time and demonstrating their potential to solve a large number of different problems, we have chosen to discuss various multivariate situations one by one and then identify the most appropriate SAS analyses for them. Many of these analyses may occasionally result from the combined applications of two or more SAS pro- cedures. All multivariate methods are illustrated by appropriate examples. In most cases, the data sets considered are real and are adapted from the published literature from a variety of disciplines. --------------------------------------------------------- Authors: Ravindra Khattree and Dayanand N. Naik Edition: 2nd Pages: 363 Please seed after your download completes. Remember that Sharing is caring.