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This text has three main purposes. The first purpose is to facilitate conceptual understanding of multivariate statistical methods by limiting the technical nature of the discussion of those concepts and focusing on their practical applications. The multivariate statistical methods covered in this text are factorial analysis of variance (ANOVA), analysis of covariance (ANCOVA), multivariat…

Structural equation modeling (SEM) : concepts, applications, and misconceptions

Structural equation modeling (SEM) is a general, cross-sectional statistical modeling technique. The chapters in this book propose a Bayesian approach based on SEM; an examination of predictors and outcomes related to school climate using latent class analysis and the testing of specific effects and contrasts in three types of mediation models followed by a discussion on the common types o…

Applied multivariate statistics for the social sciences (Sixth Edition)

This edition, like previous editions, is written for those who use, rather than develop, advanced statistical methods. The focus is on conceptual understanding rather than proving results. The narrative and many examples are there to promote understanding, and a chapter on matrix algebra is included for those who need the extra help. Through- out the book, you will find output from SPSS (ve…

Multivariate Data Analysis (Seventh Edition)

Multivariate analysis techniques are popular because they enable organizations to create knowledge and thereby improve their decision making. Multivariate analysis refers to all statistical techniques that simultaneously analyze multiple measurements on individuals or objects under investigation. Thus, any simultaneous analysis of more than two variables can be loosely considered multivariat…

Multivariate Statistics Exercises and Solutions (Second Edition)

The statistical science has seen new paradigms and more complex and richer data sets. These include data on human genomics, social networks, huge climate and weather data, and, of course, high frequency financial and economic data.

Applied Multivariate Statistical Analysis (Fourth Edition)

The fourth edition of this book on Applied Multivariate Statistical Analysis offers a new sub-chapter on Variable Selection by using least absolute shrinkage and selection operator (LASSO) and its general form the so-called Elastic Net.

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The third edition of this book on Applied Multivariate Statistical Analysis offers the following new features. 1. A new Chapter 8 on Regression Models has been added. 2. Almost all numerical examples have been reproduced in MATLAB or R. The chapter on regression models focuses on a core business of multivariate statistical analysis. This contribution has not been subject of a prominent dis…

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Multiple Regression and Beyond is designed to provide a conceptually oriented introduction to multiple regression along with more complex methods that fl ow naturally from multiple regres- sion: path analysis, confi rmatory factor analysis, and structural equation modeling. Multiple regression (MR) and related methods have become indispensable tools for modern social science researchers. MR…

Multivariate Data Analysis (Seventh Edition)

For over 30 years, Multivariate Data Analysis has provided readers with the information they need to understand and apply multivariate data analysis. Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to readers how to understand and make use of th…

Applied Multivariate Statistical Analysis (Sixth Edition)

Edisi

6th Edition

ISBN/ISSN

978-0-13-1877715-1

Deskripsi Fisik

767 hlm

Judul Seri

-

No. Panggil

EB 519.5 RIC a