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Applied Multivariate Statistics for the Social Sciences

Applied Multivariate Statistics for the Social Sciences
Author: Keenan A. Pituch
Publisher: Routledge
Total Pages: 814
Release: 2015-12-07
Genre: Psychology
ISBN: 1317805925

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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.


Applied Multivariate Statistics for the Social Sciences

Applied Multivariate Statistics for the Social Sciences
Author: James Stevens
Publisher:
Total Pages: 0
Release: 1996
Genre: Multivariate analysis
ISBN: 9780805834710

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This book was written for those who will be using, rather than developing, advanced statistical methods. It focuses on a conceptual understanding of the material rather than proving results. It is a graduate level textbook with abundant examples.


Applied Multivariate Statistics for the Social Sciences

Applied Multivariate Statistics for the Social Sciences
Author: James Paul Stevens
Publisher: Lawrence Erlbaum Associates
Total Pages: 656
Release: 1992
Genre: Mathematics
ISBN:

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This book was written for those who will be using, rather than developing, advanced statistical methods. It focuses on a conceptual understanding of the material rather than proving results. It is a graduate level textbook with abundant examples.


Handbook of Applied Multivariate Statistics and Mathematical Modeling

Handbook of Applied Multivariate Statistics and Mathematical Modeling
Author: Howard E.A. Tinsley
Publisher: Academic Press
Total Pages: 721
Release: 2000-05-22
Genre: Mathematics
ISBN: 9780080533568

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Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers to use these procedures effectively without needing to concern themselves with the mathematical basis. The Handbook emphasizes using models and statistics as tools. The objective of the book is to inform readers about which tool to use to accomplish which task. Each chapter begins with a discussion of what kinds of questions a particular technique can and cannot answer. As multivariate statistics and modeling techniques are useful across disciplines, these examples include issues of concern in biological and social sciences as well as the humanities.


Applied Multivariate Statistics for the Social Sciences, Fifth Edition

Applied Multivariate Statistics for the Social Sciences, Fifth Edition
Author: James P. Stevens
Publisher: Routledge
Total Pages: 666
Release: 2012-11-12
Genre: Education
ISBN: 1136910697

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This best-selling text is written for those who use, rather than develop statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving results. Helpful narrative and numerous examples enhance understanding and a chapter on matrix algebra serves as a review. Annotated printouts from SPSS and SAS indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use these packages, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size by providing guidelines so that the results can be generalized. The book is noted for its extensive applied coverage of MANOVA, its emphasis on statistical power, and numerous exercises including answers to half. The new edition features: New chapters on Hierarchical Linear Modeling (Ch. 15) and Structural Equation Modeling (Ch. 16) New exercises that feature recent journal articles to demonstrate the actual use of multiple regression (Ch. 3), MANOVA (Ch. 5), and repeated measures (Ch. 13) A new appendix on the analysis of correlated observations (Ch. 6) Expanded discussions on obtaining non-orthogonal contrasts in repeated measures designs with SPSS and how to make the identification of cell ID easier in log linear analysis in 4 or 5 way designs Updated versions of SPSS (15.0) and SAS (8.0) are used throughout the text and introduced in chapter 1 A book website with data sets and more. Ideal for courses on multivariate statistics found in psychology, education, sociology, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial ANOVA and covariance. Working knowledge of matrix algebra is not assumed.


Applied Multivariate Statistics for the Social Sciences

Applied Multivariate Statistics for the Social Sciences
Author: James Stevens
Publisher: Psychology Press
Total Pages: 718
Release: 1996
Genre: Education
ISBN:

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Of Important Points -- Two-Group Multivariate Analysis Of Variance -- Four Statistical Reasons for Preferring a Multivariate Analysis -- The Multivariate Test Statistic as a Generalization of Univariate t -- Numerical Calculations for a Two-Group Problem -- Three Post Hoc Procedures -- SAS and SPSS Control Lines for Sample Problem and Selected Printout -- Multivariate Significance but No Univariate Significance -- Multivariate Regression Analysis for the Sample Problem -- Power Analysis -- Ways of Improving Power -- Power Estimation on SPSS MANOVA -- Multivariate Estimation of Power -- K-Group Manova: A Priori And Post Hoc Procedures -- Multivariate Regression Analysis for a Sample Problem -- Traditional Multivariate Analysis of Variance -- Multivariate Analysis of Variance for Sample Data -- Post Hoc Procedures -- The Tukey Procedure -- Planned Comparisons -- Test Statistics for Planned Comparisons -- Multivariate Planned Comparisons on SPSS MANOVA -- Correlated Contrasts -- Studies Using Multivariate Planned Comparisons -- Stepdown Analysis -- Other Multivariate Test Statistics -- How Many Dependent Variables for a MANOVA? -- Power Analysis--A Priori Determination of Sample Size -- Novince (1977) Data for Multivariate Analysis of Variance Presented in Tables 5.3 and 5.4 -- Assumptions In Manova -- ANOVA and MANOVA Assumptions -- Independence Assumption -- What Should Be Done With Correlated Observations? -- Normality Assumption -- Multivariate Normality -- Assessing Univariate Normality -- Homogeneity of Variance Assumption.


Applied Multivariate Statistics in Geohydrology and Related Sciences

Applied Multivariate Statistics in Geohydrology and Related Sciences
Author: Charles E. Brown
Publisher: Springer Science & Business Media
Total Pages: 330
Release: 2012-12-06
Genre: Science
ISBN: 3642803288

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It has been evident from many years of research work in the geohydrologic sciences that a summary of relevant past work, present work, and needed future work in multivariate statistics with geohydrologic applications is not only desirable, but is necessary. This book is intended to serve a broad scientific audience, but more specifi cally is geared toward scientists doing studies in geohydrology and related geo sciences.lts objective is to address both introductory and advanced concepts and applications of the multivariate procedures in use today. Some of the procedures are classical in scope but others are on the forefront of statistical science and have received limited use in geohydrology or related sciences. The past three decades have seen a significant jump in the application of new research methodologies that focus on analyzing large databases. With more general applications being developed by statisticians in various disciplines, multivariate quantitative procedures are evolving for better scientific applica tion at a rapid rate and now provide for quick and informative analyses of large datasets. The procedures include a family of statistical research methods that are alternatively called "multivariate analysis" or "multivariate statistical methods".


Applied Multivariate Research

Applied Multivariate Research
Author: Lawrence S. Meyers
Publisher: SAGE Publications
Total Pages: 938
Release: 2016-10-28
Genre: Social Science
ISBN: 1506329780

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Using a conceptual, non-mathematical approach, the updated Third Edition provides full coverage of the wide range of multivariate topics that graduate students across the social and behavioral sciences encounter. Authors Lawrence S. Meyers, Glenn Gamst, and A. J. Guarino integrate innovative multicultural topics in examples throughout the book, which include both conceptual and practical coverage of: statistical techniques of data screening; multiple regression; multilevel modeling; exploratory factor analysis; discriminant analysis; structural equation modeling; structural equation modeling invariance; survival analysis; multidimensional scaling; and cluster analysis.


Applied Multivariate Statistics for the Social Sciences

Applied Multivariate Statistics for the Social Sciences
Author: Keenan A. Pituch
Publisher: Routledge
Total Pages: 827
Release: 2015-12-07
Genre: Psychology
ISBN: 1317805917

Download Applied Multivariate Statistics for the Social Sciences Book in PDF, ePub and Kindle

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.


Applied Multivariate Statistics with R

Applied Multivariate Statistics with R
Author: Daniel Zelterman
Publisher: Springer Nature
Total Pages: 469
Release: 2023-01-20
Genre: Medical
ISBN: 3031130057

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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.