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The book is aimed at applied statisticians, graduate students of statistics, and students and researchers with a strong interest;
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Applied Multivariate Statistical Analysis, is a book that is intended for university students of any college. You'll find theory as;
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applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it;
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applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it;
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multivariate statistical methods, as well as select nonparametric tests. Altogether a hands-on manual on the applied statistics and essential R;
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Today, through the sophistication of statistical software packages such as SPSS, virtually all graduate students across the social and;
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This book on multivariate models, statistical inference, and data analysis contains deep coverage of multivariate non-normal distributions;
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statistics courses as well as for professionals who require an understanding of statistical techniques for analyzing their own data sets. Focused on;
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offers a readable introduction to the statistical analysis of multivariate observations. Its primary goal is to impart the knowledge necessary to;
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applied resources at various levels, the book includes statistical techniques using software packages such as R and SPSS (R). To promote a more;
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This book expands on the classical statistical multivariate analysis theory by focusing on bilinear regression models, a class of models;
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Statistical Analysis of Management Data provides a comprehensive approach to multivariate statistical analyses that are important for;
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A modern approach to statistical learning and its applications through visualization methods With a unique and innovative presentation;
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graduate and postgraduate students undertaking statistical analysis for business degrees, providing an application-oriented introduction to;
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statistical analyses and data management tasks in Python Applied Univariate, Bivariate, and Multivariate Statistics Using Python delivers a;
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underlying patterns and structure. This intermediate-level textbook introduces the reader to the variety of methods by which multivariate statistical;
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, during which both methodological and applied statistical research was discussed. This selection of fully peer-reviewed papers, originally;
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statistical packages (e.g., SAS, SPSS).;
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Advanced and Multivariate Statistical Methods, Seventh Edition provides conceptual and practical information regarding multivariate;
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Advanced and Multivariate Statistical Methods, Seventh Edition provides conceptual and practical information regarding multivariate;
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Using formal descriptions, graphical illustrations, practical examples, and R software tools, Introduction to Multivariate Statistical;
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variable selection. For advanced undergraduate and graduate students in statistical science, this text provides a systematic description;
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variable selection. For advanced undergraduate and graduate students in statistical science, this text provides a systematic description of both;
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The most accessible introduction to the theory and practice of multivariate analysis Multivariate Statistical Inference and Applications;
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the necessary mathematical foundations of applied multivariate analysis. It brings up-to-date many definitions of mathematical concepts and;
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applications-oriented introduction to multivariate analysis greatly reduces the amount of statistical notation and terminology used while focusing;
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surveys of developments in multivariate statistical analysis and gives statistically sound coverage of the subject. The contributors are all;
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