Description
Book SynopsisApplied Statistics presents a thorough treatment of the methods of regression and analysis of variance. The book focuses on conceptual understandings of statistical methods in regression and analysis of variance as well as the use of statistical software to obtain correct results. Real data examples from many fields of study are used to motivate the presentation and illustrate the concepts and methods. Almost all of the examples in the book are accompanied with their corresponding SAS programs. The R programs are available on the following website: http://people.cst.cmich.edu/famoy1kf/appliedstat. This textbook is user-friendly and simplifies the presentation of complicated material. Applied Statistics requires an understanding of introductory statistics courses and is suitable for both junior and senior undergraduate students.
Trade ReviewApplied Statistics . . . extensive coverage of regression and analysis of variance techniques combined with its exemplary demonstration of SAS coding through examples make it a valuable resource for a variety of statistics users. . . [W]hile Applied Statistics could effectively be used as a course textbook . . . [I]t may be even more attractive to researchers for use as a reference tool. * The American Statistician *
Table of Contents1: Introduction 2: Simple Linear Regression 3: Inferences on Parameter Estimates 4: Mutiple Linear Regression 5: Regression Diagnostics and Remedial Methods 6: Multiple and Partial Correlations 7: Model Selection Strategies 8: Use of Dummy Variables in Regression Analysis 9: Polynomial Regression 10: Logistic Regression 11: Count Data Regression Models 12: Regression with Censored of Truncated Data 13: Nonlinear Regression 14: One-Way Analysis of Variance 15: Two-Factor Analysis of Variance 16: Analysis of Covariance 17: Randomized Complete Block Design 18: Non Orthogonal Classification
