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Design and analysis of experiments in the health sciences / Gerald van Belle, Kathleen F. Kerr.

By: Contributor(s): Material type: TextTextPublication details: Hoboken, N.J. : Wiley, 2012.Edition: 1st edDescription: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781118279694
  • 1118279697
  • 9786613678904
  • 6613678902
  • 9781118279724
  • 1118279727
  • 1280768134
  • 9781280768132
Subject(s): Genre/Form: Additional physical formats: Print version:: Design and analysis of experiments in the health sciences.DDC classification:
  • 610.72/7 23
LOC classification:
  • R858 .V36 2012eb
Other classification:
  • MAT029000
Online resources:
Contents:
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.
Summary: "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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"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.

Includes bibliographical references and index.

Print version record.

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.

Life Sciences