Analysis of Variance for Random Models, Volume 2: Unbalanced Data : Theory, Methods, Applications, and Data Analysis
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The work Analysis of Variance for Random Models, Volume 2: Unbalanced Data : Theory, Methods, Applications, and Data Analysis represents a distinct intellectual or artistic creation found in University of Oklahoma Libraries. This resource is a combination of several types including: Work, Language Material, Books.
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Analysis of Variance for Random Models, Volume 2: Unbalanced Data : Theory, Methods, Applications, and Data Analysis
Resource Information
The work Analysis of Variance for Random Models, Volume 2: Unbalanced Data : Theory, Methods, Applications, and Data Analysis represents a distinct intellectual or artistic creation found in University of Oklahoma Libraries. This resource is a combination of several types including: Work, Language Material, Books.
 Label
 Analysis of Variance for Random Models, Volume 2: Unbalanced Data : Theory, Methods, Applications, and Data Analysis
 Title remainder
 Theory, Methods, Applications, and Data Analysis
 Statement of responsibility
 by Hardeo Sahai, Mario M. Ojeda
 Language

 eng
 eng
 Summary
 Analysis of variance (ANOVA) models have become widely used tools and play a fundamental role in much of the application of statistics today. In particular, ANOVA models involving random effects have found widespread application to experimental design in a variety of fields requiring measurements of variance, including agriculture, biology, animal breeding, applied genetics, econometrics, quality control, medicine, engineering, and social sciences. This twovolume work is a comprehensive presentation of different methods and techniques for point estimation, interval estimation, and tests of hypotheses for linear models involving random effects. Both Bayesian and repeated sampling procedures are considered. Volume I examines models with balanced data (orthogonal models); Volume II studies models with unbalanced data (nonorthogonal models). Features and Topics: * Systematic treatment of the commonly employed crossed and nested classification models used in analysis of variance designs * Detailed and thorough discussion of certain random effects models not commonly found in texts at the introductory or intermediate level * Numerical examples to analyze data from a wide variety of disciplines * Many worked examples containing computer outputs from standard software packages such as SAS, SPSS, and BMDP for each numerical example * Extensive exercise sets at the end of each chapter * Numerous appendices with background reference concepts, terms, and results * Balanced coverage of theory, methods, and practical applications * Complete citations of important and related works at the end of each chapter, as well as an extensive general bibliography Accessible to readers with only a modest mathematical and statistical background, the work will appeal to a broad audience of students, researchers, and practitioners in the mathematical, life, social, and engineering sciences. It may be used as a textbook in upperlevel undergraduate and graduate courses, or as a reference for readers interested in the use of random effects models for data analysis
 Dewey number
 519.538
 http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsaut

 6AfBzw0vhZU
 xDCBrSoEgiQ
 Language note
 English
 LC call number

 QA273.A1274.9
 QA274274.9
 Literary form
 non fiction
 Nature of contents
 dictionaries
 Series statement
 Analysis of variance for random models
 Series volume
 v.2
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