Includes bibliographical references and index.

Design and Analysis of Experiments in the Health Sciences; Contents; Preface; 1 The Basics; 1.1 Four Basic Questions; 1.2 Variation; 1.3 Principles of Design and Analysis; 1.4 Experiments and Observational Studies; 1.5 Illustrative Applications of Principles; 1.6 Experiments in the Health Sciences; 1.7 Adaptive Allocation; 1.7.1 Equidistribution; 1.7.2 Adaptive Allocation Techniques; 1.8 Sample Size Calculations; 1.9 Statistical Models for the Data; 1.10 Analysis and Presentation; 1.10.1 Graph the Data in Several Ways; 1.10.2 Assess Assumptions of the Statistical Model.

"This volume provides technical professionals and students with three uniquely integrative enhancements to the study of predictive modeling not typically found in data-mining books: an applied approach, immediate practice using Microsoft Excel, and easy-to-use access to multiple online model-building tools. Since actual datasets are employed, users deal with real-life modeling issues and situations such as handling missing values, applying variable transformations, and addressing outliers, among others. An easy-to-learn Microsoft Excel add-in (Predictive MinerXL) and all applicable datasets are available for free on an associated Web site"-- Provided by publisher.

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