Regression Analysis provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose of statistical analyses, to allow the student to determine, at least to some degree, the correct type of statistical analyses to be performed in a given situation, and have some appreciation of what constitutes good experimental design.

Regression Analysis: Statistical Modeling of a Response Variable

Science & Math

Wilson, William J.

Freund, Rudolf J.

Sa, Ping

Mathematics

Academic Press

Aimed at upper-division undergraduates majoring in statistics, as well as graduate students from a variety of disciplines (business, psychology, education, and sociology) who need to use sophisticated statistical methods in their research and other professional activities. This is a comprehensive textbook for a course in statistical methods, primarily aimed at majors other than statistics in upper-division undergraduate- and graduate level courses. The use of this book in a two-semester course sequence provides a complete overview of most standard statistical methods, including a substantial amount of material on multiple regression, analysis of variance, experimental design, and sampling techniques. In addition, the text is organized in a manner to provide a useful subset of methods is used for only one semester. The primary purpose throughout is to teach intelligent data analysis and principles of good data collection, including the intelligent use of computers to assist in drawing conclusions about data. The only mathematical background necessary is two years of school algebra. Features include a comprehensive overview of most standard statistical methods - multiple regression, analysis of variance, experimental design, and sampling techniques; a useful subset of methods if used for only one semester; learning concepts as opposed to the "plugging numbers into formulas" approach.

Statistical Methods

Reference

Academic Pr

This expansive text provides a complete overview of the majority of standard statistical methods, including a substantial amount of material on multiple regression, analysis of variance, experimental design, and sampling techniques. Revised and updated, Statistical Methods is a comprehensive textbook intended for students in a major other than statistics. Assuming a background of only two years of high school algebra, Statistical Methods, Revised Edition, teaches intelligent data analysis and covers the principles of good data collection. The book details the use of computers to assist in drawing conclusions about data and has additional drill-type exercises at the end of the chapter problem sets in order to give students a chance to build confidence before moving on to the more difficult problems. Applications have also been integrated throughout the text in new sections. * Completely revised and updated since the First Edition * Provides a comprehensive overview of most standard statistical methods--multiple regression, analysis of variance, experimental design, and sampling techniques * Emphasizes learning concepts as opposed to the plugging numbers into formulas approach

Statistical Methods : Revised Edition

This broad text provides a complete overview of most standard statistical methods, including multiple regression, analysis of variance, experimental design, and sampling techniques. Assuming a background of only two years of high school algebra, this book teaches intelligent data analysis and covers the principles of good data collection.

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Regression Analysis Study Guide

Health, Fitness & Dieting

Mental Health

Elsevier Science

Statistical Methods, Fourth Edition, is designed to introduce students to a wide-range of popular and practical statistical techniques. Requiring a minimum of advanced mathematics, it is suitable for undergraduates in statistics, or graduate students in the physical, life, and social sciences. By providing an overview of statistical reasoning, this text equips readers with the insight needed to summarize data, recognize good experimental designs, implement appropriate analyses, and arrive at sound interpretations of statistical results.

Mohr, Donna L.

This clear and comprehensive guide provides everything you need for powerful linear model analysis. Using a tutorial approach and plenty of examples, authors Ramon Littell, Walter Stroup, and Rudolf Freund lead you through methods related to analysis of variance with fixed and random effects. You will learn to use the appropriate SAS procedure for most experiment designs (including completely random, randomized blocks, and split plot) as well as factorial treatment designs and repeated measures. SAS for Linear Models, Fourth Edition, also includes analysis of covariance, multivariate linear models, and generalized linear models for non-normal data. Find inside: regression models; balanced ANOVA with both fixed- and random-effects models; unbalanced data with both fixed- and random-effects models; covariance models; generalized linear models; multivariate models; and repeated measures. New in this edition: MIXED and GENMOD procedures, updated examples, new software-related features, and other new material. This book is part of the SAS Press program.

SAS for Linear Models, Fourth Edition

Computers & Technology

Littell, Ramon C.

Stroup, Walter W.

Computer Science

SAS Institute

See the best price to sell, buy, or rent books by Freund, Rudolf J.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Freund, Rudolf J.

See the best price to sell, buy, or rent books by Freund, Rudolf J.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Regression Analysis: Statistical Modeling of a Response Variable

Statistical Methods

Statistical Methods : Revised Edition

Statistical Methods

Regression Analysis Study Guide

Statistical Methods

SAS for Linear Models, Fourth Edition