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An Introduction to the Analysis of Variance

Autor Richard S. Bogartz
en Limba Engleză Hardback – 16 ian 1994 – vârsta până la 17 ani
This book is for students taking either a first-year graduate statistics course or an advanced undergraduate statistics course in Psychology. Enough introductory statistics is briefly reviewed to bring everyone up to speed. The book is highly user-friendly without sacrificing rigor, not only in anticipating students' questions, but also in paying attention to the introduction of new methods and notation. In addition, many topics given only casual or superficial treatment are elaborated here, such as: the nature of interaction and its interpretation, in terms of theory and response scale transformations; generalized forms of analysis of covariance; extensive coverage of multiple comparison methods; coverage of nonorthogonal designs; and discussion of functional measurement. The text is structured for reading in multiple passes of increasing depth; for the student who desires deeper understanding, there are optional sections; for the student who is or becomes proficient in matrix algebra, there are still deeper optional sections. The book is also equipped with an excellent set of class-tested exercises and answers.
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Specificații

ISBN-13: 9780275947200
ISBN-10: 0275947203
Pagini: 582
Dimensiuni: 156 x 235 x 32 mm
Greutate: 0.98 kg
Ediția:New.
Editura: Bloomsbury Publishing
Colecția Praeger
Locul publicării:New York, United States

Notă biografică

Richard S. Bogartz is professor of psychology at the University of Massachusetts, Amherst. He has taught at the University of Illinois, the University of Iowa, and received his PhD at UCLA. He is the author of numerous articles in a variety of journals, including Journal of Experimental Psychology, Journal of Mathematical Psychology, Journal of Experimental Child Psychology, Psychological Bulletin, Perception & Psychophysics, and others.

Cuprins

PreliminariesWhat We Do in an ANOVASome Geometry of the ANOVATwo Factor Designs and Three Factor DesignsComputations and DisplayNested FactorsRandom Effects ModelsRepeated Measurement DesignsContrasting EffectsTrend TestsMultiple ComparisonsRegression, ANOVA, and the General Linear ModelSome Fine PointsSome Advanced ApplicationsNonorthogonal DesignsExperimental DesignAppendix 1: Random Variables and Their ExpectationsAppendix 2: Vectors and MatricesAppendix 3: Statistical Tables and ChartsReferencesIndex