Understanding Regression Analysis by Michael Patrick Allen (English) Paperback B

Description: Understanding Regression Analysis by Michael Patrick Allen By assuming it is possible to understand regression analysis without fully comprehending all its underlying proofs and theories, this introduction to the widely used statistical technique is accessible to readers who may have only a rudimentary knowledge of mathematics. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description By assuming it is possible to understand regression analysis without fully comprehending all its underlying proofs and theories, this introduction to the widely used statistical technique is accessible to readers who may have only a rudimentary knowledge of mathematics. Chapters discuss:-descriptive statistics using vector notation and the components of a simple regression model;-the logic of sampling distributions and simple hypothesis testing; -the basic operations of matrix algebra and the properties of the multiple regression model; -testing compound hypotheses and the application of the regression model to the analyses of variance and covariance, and -structural equation models and influence statistics. Notes Springer Book Archives Table of Contents The origins and uses of regression analysis.- Basic matrix algebra: Manipulating vectors.- The mean and variance of a variable.- Regression models and linear functions.- Errors of prediction and least-squares estimation.- Least-squares regression and covariance.- Covariance and linear independence.- Separating explained and error variance.- Transforming variables to standard form.- Regression analysis with standardized variables.- Populations, samples, and sampling distributions.- Sampling distributions and test statistics.- Testing hypotheses using the t test.- The t test for the simple regression coefficient.- More matrix algebra: Manipulating matrices.- The multiple regression model.- Normal equations and partial regression coefficients.- Partial regression and residualized variables.- The coefficient of determination in multiple regression.- Standard errors of partial regression coefficients.- The incremental contributions of variables.- Testing simple hypotheses using the F test.- Testing compound hypotheses using the F test.- Testing hypotheses in nested regression models.- Testing for interaction in multiple regression.- Nonlinear relationships and variable transformations.- Regression analysis with dummy variables.- One-way analysis of variance using the regression model.- Two-way analysis of variance using the regression model.- Testing for interaction in analysis of variance.- Analysis of covariance using the regression model.- Interpreting interaction in analysis of covariance.- Structural equation models and path analysis.- Computing direct and total effects of variables.- Model specification in regression analysis.- Influential cases in regression analysis.- The problem of multicollinearity.- Assumptions of ordinary least-squares estimation.- Beyond ordinary regression analysis. Review "Allens book will, no doubt, earn the praises of statistics instructors and students alike...Provides the reader a thorough, yet lucid, journey through a variety of statistical concepts...This gem should be made a part of every prospective statisticians collection. Undergraduates through professional." (Choice, March 1998) Promotional Springer Book Archives Long Description By assuming it is possible to understand regression analysis without fully comprehending all its underlying proofs and theories, this introduction to the widely used statistical technique is accessible to readers who may have only a rudimentary knowledge of mathematics. Chapters discuss: -descriptive statistics using vector notation and the components of a simple regression model; -the logic of sampling distributions and simple hypothesis testing; -the basic operations of matrix algebra and the properties of the multiple regression model; -testing compound hypotheses and the application of the regression model to the analyses of variance and covariance, and -structural equation models and influence statistics. Review Text "Allens book will, no doubt, earn the praises of statistics instructors and students alike...Provides the reader a thorough, yet lucid, journey through a variety of statistical concepts...This gem should be made a part of every prospective statisticians collection. Undergraduates through professional." (Choice, March 1998) Review Quote "Allens book will, no doubt, earn the praises of statistics instructors and students alike...Provides the reader a thorough, yet lucid, journey through a variety of statistical concepts...This gem should be made a part of every prospective statisticians collection. Undergraduates through professional." (Choice, March 1998) Details ISBN0306484331 Author Michael Patrick Allen Short Title UNDERSTANDING REGRESSION ANALY Language English ISBN-10 0306484331 ISBN-13 9780306484339 Media Book Format Paperback Year 2004 Publication Date 2004-05-31 DEWEY 519.536 Edition 1st Place of Publication New York Country of Publication United States Pages 216 Imprint Kluwer Academic/Plenum Publishers Illustrations XII, 216 p. DOI 10.1007/b107535;10.1007/978-0-585-25657-3;10.1007/b102242 UK Release Date 2004-05-31 AU Release Date 2004-05-31 NZ Release Date 2004-05-31 US Release Date 2004-05-31 Publisher Springer Science+Business Media Edition Description Softcover reprint of the original 1st ed. 1997 Alternative 9780306456480 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:137947985;

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