George A. Milliken, Dallas E. Johnson

Analysis of Messy Data Volume 1 (eBook, ePUB)

Designed Experiments, Second Edition

• Format: ePub

Produktbeschreibung

A bestseller for nearly 25 years, Analysis of Messy Data, Volume 1: Designed Experiments helps applied statisticians and researchers analyze the kinds of data sets encountered in the real world. Written by two long-time researchers and professors, this second edition has been fully updated to reflect the many developments that have occurred since t

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 674
• Erscheinungstermin: 2. März 2009
• Englisch
• ISBN-13: 9781040066522
• Artikelnr.: 73256740

Autorenporträt

George A. Milliken, Dallas E. Johnson

Inhaltsangabe

The Simplest Case: One-Way Treatment Structure in a Completely Randomized
Design Structure with Homogeneous Errors. One-Way Treatment Structure in a
Completely Randomized Design Structure with Heterogeneous Errors.
Simultaneous Inference Procedures and Multiple Comparisons. Basics for
Designing Experiments. Multilevel Designs: Split-Plots, Strip-Plots,
Repeated Measures, and Combinations. Matrix Form of the Model. Balanced
Two-Way Treatment Structures. Case Study: Complete Analyses of Balanced
Two-Way Experiments. Using the Means Model to Analyze Balanced Two-Way
Treatment Structures with Unequal Subclass Numbers. Using the Effects Model
to Analyze Balanced Two-Way Treatment Structures with Unequal Subclass
Numbers. Analyzing Large Balanced Two-Way Experiments Having Unequal
Subclass Numbers. Case Study: Balanced Two-Way Treatment Structure with
Unequal Subclass Numbers. Using the Means Model to Analyze Two-Way
Treatment Structures with Missing Treatment Combinations. Using the Effects
Model to Analyze Two-Way Treatment Structures with Missing Treatment
Combinations. Case Study: Two-Way Treatment Structure with Missing
Treatment Combinations. Analyzing Three-Way and Higher-Order Treatment
Structures. Case Study: Three-Way Treatment Structure with Many Missing
Treatment Combinations. Random Effects Models and Variance Components.
Methods for Estimating Variance Components. Methods for Making Inferences
about Variance Components. Case Study: Analysis of a Random Effects Model.
Analysis of Mixed Models. Case Studies of a Mixed Model. Methods for
Analyzing Split-Plot Type Designs. Methods for Analyzing Strip-Plot Type
Designs. Methods for Analyzing Repeated Measures Experiments. Analysis of
Repeated Measures Experiments When the Ideal Conditions Are Not Satisfied.
Case Studies: Complex Examples Having Repeated Measures. Analysis of
Crossover Designs. Analysis of Nested Designs. Appendix. Index.