Introduction to Linear Models and Statistical Inference

Steven J. Janke, Frederick C. Tinsley

584 pages, parution le 29/08/2005

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Résumé

A multidisciplinary approach that emphasizes learning by analyzing real-world data sets

This book is the result of the authors' hands-on classroom experience and is tailored to reflect how students best learn to analyze linear relationships. The text begins with the introduction of four simple examples of actual data sets. These examples are developed and analyzed throughout the text, and more complicated examples of data sets are introduced along the way. Taking a multidisciplinary approach, the book traces the conclusion of the analyses of data sets taken from geology, biology, economics, psychology, education, sociology, and environmental science.

As students learn to analyze the data sets, they master increasingly sophisticated linear modeling techniques, including:

Simple linear models
Multivariate models
Model building
Analysis of variance (ANOVA)
Analysis of covariance (ANCOVA)
Logistic regression
Total least squares

The basics of statistical analysis are developed and emphasized, particularly in testing the assumptions and drawing inferences from linear models. Exercises are included at the end of each chapter to test students' skills before moving on to more advanced techniques and models. These exercises are marked to indicate whether calculus, linear algebra, or computer skills are needed.

Unlike other texts in the field, the mathematics underlying the models is carefully explained and accessible to students who may not have any background in calculus or linear algebra. Most chapters include an optional final section on linear algebra for students interested in developing a deeper understanding.

The many data sets that appear in the text are available on the book's Web site. The MINITAB(r) software program is used to illustrate many of the examples. For students unfamiliar with MINITAB(r), an appendix introduces the key features needed to study linear models.

With its multidisciplinary approach and use of real-world data sets that bring the subject alive, this is an excellent introduction to linear models for students in any of the natural or social sciences.

L'auteur - Steven J. Janke

Steven J. JankeE, PHD, and Frederick C. Tinsley, PHD, are both Professors of Mathematics at Colorado College, Colorado Springs. Both Dr. Janke and Dr. Tinsley have been teaching linear models courses for more than two decades.

L'auteur - Frederick C. Tinsley

Sommaire

Introduction: Statistical Questions
Data: Plots and Location
Data: Dispersion and Correlation
Random Variables: Probability and Density
Random Variables: Expectation and Variance
Statistical Inference
Simple Linear Models
Linear Model Diagnostics
Linear Models: Two Independent Variables
Linear Models: Several Independent Variables
Model Building
Extended Linear Models
Appendix A: Data References
Appendix B: MINITAB Reference
Appendix C: Introduction to Linear Algebra
Appendix D: Statistical Tables
References
Index

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	Steven J. Janke, Frederick C. Tinsley
Parution	29/08/2005
Nb. de pages	584
Format	16 x 24
Couverture	Relié
Poids	936g
Intérieur	Noir et Blanc
EAN13	9780471662594
ISBN13	978-0-471-66259-4