Applied Multivariate Data Analysis is an essential resource for anyone seeking a comprehensive introduction to the analysis of complex, multivariable datasets. This intermediate textbook skillfully breaks down the challenges of simultaneous variable examination and provides clear, accessible explanations of various multivariate statistical techniques. The authors guide the reader through exploring and describing data, uncovering the hidden patterns and structures within what might initially seem like overwhelming information. Now in its updated edition, this book includes revised chapters and new sections that address modern methods such as neural networks and random effects models for longitudinal data. With its easy-to-understand style, plentiful examples, and supportive figures, Applied Multivariate Data Analysis is ideally suited for students in applied statistics as well as researchers across diverse fields. The numerous exercises included in each chapter further enhance the reader’s ability to master multivariate analytical methods.
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