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Author : Ravindra Khattree
Publisher : Unknown
Page : 128 pages
File Size : 53,8 Mb
Release : 2003
Category : Multivariate analysis
ISBN : OCLC:1136879504
Author : Ravindra Khattree,Dayanand N. Naik
Publisher : Unknown
Page : 396 pages
File Size : 49,7 Mb
Release : 1999
Category : SAS (Computer file)
ISBN : OCLC:641845921
Author : Ravindra Khattree,Dayanand N. Naik
Publisher : Unknown
Page : 368 pages
File Size : 47,5 Mb
Release : 2018-07
Category : Computers
ISBN : 1635269202
Real-world problems and data sets are the backbone of Ravindra Khattree and Dayanand Naik's Applied Multivariate Statistics with SAS Software, Second Edition, which provides a unique approach to the topic, integrating statistical methods, data analysis, and applications. Now extensively revised, the book includes new information about mixed effects models, applications of the MIXED procedure, regression diagnostics with the corresponding IML procedure code, and covariance structures. The authors' approach to the information will aid professors, researchers, and students in a variety of disciplines and industries. Extensive SAS code and the corresponding high-resolution output accompany sample problems, and clear explanations of SAS procedures are included. Emphasis is on correct interpretation of the output to draw meaningful conclusions. Featuring both the theoretical and the practical, topics covered include multivariate analysis of experimental data and repeated measures data, graphical representation of data including biplots, and multivariate regression. In addition, a quick introduction to the IML procedure with special reference to multivariate data is available in an appendix. SAS programs and output integrated with the text make it easy to read and follow the examples. This book is part of the SAS Press program.
Author : Ravindra Khattree,Dayanand N. Naik
Publisher : Wiley-Interscience
Page : 0 pages
File Size : 47,7 Mb
Release : 2008-03-14
Category : Mathematics
ISBN : 0470388056
This set contains 9780471322993 Applied Multivariate Statistics with SAS? Software, 2nd Edition and 9780471323006 Multivariate Data Reduction and Discrimination with SAS? Software both by Ravindra Khattree and Dayanand N. Naik.
Author : Ravindra Khattree,Dayanand N. Naik
Publisher : Wiley-SAS
Page : 0 pages
File Size : 47,6 Mb
Release : 2000-08-14
Category : Mathematics
ISBN : 0471323004
Easy to read and comprehensive, this book presents descriptive multivariate (DMV) statistical methods using real-world problems and data sets. It offers a unique approach to integrating statistical methods, various kinds of advanced data analyses, and applications of the popular SAS software aids. Emphasis is placed on the correct interpretation of output to draw meaningful conclusions in a variety of disciplines and industries.
Author : Keenan A. Pituch,James P. Stevens
Publisher : Routledge
Page : 827 pages
File Size : 48,7 Mb
Release : 2015-12-07
Category : Psychology
ISBN : 9781317805915
Now in its 6th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies. With the added expertise of co-author Keenan Pituch (University of Texas-Austin), this 6th edition retains many key features of the previous editions, including its breadth and depth of coverage, a review chapter on matrix algebra, applied coverage of MANOVA, and emphasis on statistical power. In this new edition, the authors continue to provide practical guidelines for checking the data, assessing assumptions, interpreting, and reporting the results to help students analyze data from their own research confidently and professionally. Features new to this edition include: NEW chapter on Logistic Regression (Ch. 11) that helps readers understand and use this very flexible and widely used procedure NEW chapter on Multivariate Multilevel Modeling (Ch. 14) that helps readers understand the benefits of this "newer" procedure and how it can be used in conventional and multilevel settings NEW Example Results Section write-ups that illustrate how results should be presented in research papers and journal articles NEW coverage of missing data (Ch. 1) to help students understand and address problems associated with incomplete data Completely re-written chapters on Exploratory Factor Analysis (Ch. 9), Hierarchical Linear Modeling (Ch. 13), and Structural Equation Modeling (Ch. 16) with increased focus on understanding models and interpreting results NEW analysis summaries, inclusion of more syntax explanations, and reduction in the number of SPSS/SAS dialogue boxes to guide students through data analysis in a more streamlined and direct approach Updated syntax to reflect newest versions of IBM SPSS (21) /SAS (9.3) A free online resources site at www.routledge.com/9780415836661 with data sets and syntax from the text, additional data sets, and instructor’s resources (including PowerPoint lecture slides for select chapters, a conversion guide for 5th edition adopters, and answers to exercises) Ideal for advanced graduate-level courses in education, psychology, and other social sciences in which multivariate statistics, advanced statistics, or quantitative techniques courses are taught, this book also appeals to practicing researchers as a valuable reference. Pre-requisites include a course on factorial ANOVA and covariance; however, a working knowledge of matrix algebra is not assumed.
Author : Neil H. Timm
Publisher : Springer Science & Business Media
Page : 709 pages
File Size : 50,7 Mb
Release : 2007-06-21
Category : Mathematics
ISBN : 9780387227719
This book provides a broad overview of the basic theory and methods of applied multivariate analysis. The presentation integrates both theory and practice including both the analysis of formal linear multivariate models and exploratory data analysis techniques. Each chapter contains the development of basic theoretical results with numerous applications illustrated using examples from the social and behavioral sciences, and other disciplines. All examples are analyzed using SAS for Windows Version 8.0.
Author : Tenko Raykov,George A. Marcoulides
Publisher : Routledge
Page : 487 pages
File Size : 50,7 Mb
Release : 2008-03-10
Category : Business & Economics
ISBN : 9781136676000
This comprehensive text introduces readers to the most commonly used multivariate techniques at an introductory, non-technical level. By focusing on the fundamentals, readers are better prepared for more advanced applied pursuits, particularly on topics that are most critical to the behavioral, social, and educational sciences. Analogies betwe
Author : Ravindra Khattree,Dayanand N. Naik
Publisher : Sas Inst
Page : 396 pages
File Size : 54,8 Mb
Release : 1995
Category : Mathematics
ISBN : 1555442390
Author : Ronald P. Cody,Jeffrey K. Smith
Publisher : Unknown
Page : 432 pages
File Size : 49,7 Mb
Release : 1991
Category : Computers
ISBN : UOM:39015058318893
Author : Daniel Zelterman
Publisher : Springer Nature
Page : 469 pages
File Size : 40,8 Mb
Release : 2023-01-20
Category : Medical
ISBN : 9783031130052
Now in its second edition, this book brings multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source shareware program R, Dr. Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays; linear algebra; univariate, bivariate and multivariate normal distributions; factor methods; linear regression; discrimination and classification; clustering; time series models; and additional methods. He uses practical examples from diverse disciplines, to welcome readers from a variety of academic specialties. Each chapter includes exercises, real data sets, and R implementations. The book avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary. New to this edition are chapters devoted to longitudinal studies and the clustering of large data. It is an excellent resource for students of multivariate statistics, as well as practitioners in the health and life sciences who are looking to integrate statistics into their work.
Author : Mervyn G. Marasinghe,William J. Kennedy
Publisher : Springer Science & Business Media
Page : 562 pages
File Size : 46,5 Mb
Release : 2008-12-10
Category : Mathematics
ISBN : 9780387773728
This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate majors or advanced undergraduate students from a variety of disciplines. These students typically have taken an introductory-level s- tistical methods course that requires the use a software system such as SAS for performing statistical analysis. Thus students are expected to have an - derstanding of basic concepts of statistical inference such as estimation and hypothesis testing. Understandably, adequate time is not available in a ?rst course in stat- tical methods to cover the use of a software system adequately in the amount of time available for instruction. The aim of this book is to teach how to use the SAS system for data analysis. The SAS language is introduced at a level of sophistication not found in most introductory SAS books. Important features such as SAS data step programming, pointers, and line-hold spe- ?ers are described in detail. The powerful graphics support available in SAS is emphasized throughout, and many worked SAS program examples contain graphic components.
Author : Norm O'Rourke,Larry Hatcher,Edward J. Stepanski,SAS Institute, Inc.
Publisher : Wiley-SAS
Page : 550 pages
File Size : 41,5 Mb
Release : 2005-08-12
Category : Mathematics
ISBN : 0471469440
One in a series of books co-published with SAS, this book provides a user-friendly introduction to both the SAS system and elementary statistical procedures for researchers and students in the Social Sciences. This Second Edition, updated to cover version 9 of the SAS software, guides readers step by step through the basic concepts of research and data analysis, to data input, and on to ANOVA (analysis of variance) and MANOVA (multivariate analysis of variance).
Author : Brian Everitt,Torsten Hothorn
Publisher : Springer Science & Business Media
Page : 284 pages
File Size : 46,6 Mb
Release : 2011-04-23
Category : Mathematics
ISBN : 9781441996503
The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.
Author : Keenan A. Pituch,James Paul Stevens
Publisher : Unknown
Page : 793 pages
File Size : 43,5 Mb
Release : 2016
Category : Multivariate analysis
ISBN : 1315814919