Search Results for "applied-multivariate-statistical-analysis"

Applied Multivariate Statistical Analysis

Applied Multivariate Statistical Analysis

  • Author: Richard Arnold Johnson,Dean W. Wichern
  • Publisher: N.A
  • ISBN: 9781292024943
  • Category: Mathematical analysis
  • Page: 776
  • View: 9441
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This market leader offers a readable introduction to the statistical analysis of multivariate observations. Gives readers the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Starts with a formulation of the population models, delineates the corresponding sample results, and liberally illustrates everything with examples. Offers an abundance of examples and exercises based on real data. Appropriate for experimental scientists in a variety of disciplines.

Applied Multivariate Statistical Analysis

Applied Multivariate Statistical Analysis

  • Author: Wolfgang Karl Härdle,Léopold Simar
  • Publisher: Springer Science & Business Media
  • ISBN: 3662058022
  • Category: Mathematics
  • Page: 486
  • View: 8129
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A state of the art presentation of the tools and concepts of multivariate data analysis with a strong focus on applications. The first part is devoted to graphical techniques describing the distributions of the involved variables. The second part deals with multivariate random variables and presents distributions, estimators and tests for various practical situations. The last part covers mulivariate techniques and introduces the reader into the wide variety of tools for multivariate data analysis. The text presents a wide range of examples and 228 exercises.

Applied Multivariate Statistical Analysis

Applied Multivariate Statistical Analysis

  • Author: Richard A. Johnson,Richard Arnold Johnson,Dean W. Wichern
  • Publisher: N.A
  • ISBN: N.A
  • Category: Analyse multivariée
  • Page: 642
  • View: 3254
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Explores the statistical methods for describing and analyzing multivariate data. It's goal is to provide readers with the knowledge necessary to make proper interpretations, and select appropriate techniques for analyzing multivariate data Coverage includes: Detecting Outliers and Data Cleaning; Multivariate Quality Control; Monitoring Quality with Principal Components; and Correspondence Analysis, Biplots, and Procrustes Analysis.

Applied Multivariate Statistical Analysis

Applied Multivariate Statistical Analysis

  • Author: Wolfgang Härdle,Léopold Simar
  • Publisher: Springer Science & Business Media
  • ISBN: 3540722432
  • Category: Business & Economics
  • Page: 458
  • View: 2390
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With a wealth of examples and exercises, this is a brand new edition of a classic work on multivariate data analysis. A key advantage of the work is its accessibility as it presents tools and concepts in a way that is understandable for non-mathematicians.

Applied Multivariate Statistics for the Social Sciences

Applied Multivariate Statistics for the Social Sciences

  • Author: James Paul Stevens
  • Publisher: Taylor & Francis
  • ISBN: 0805859012
  • Category: Social Science
  • Page: 651
  • View: 7236
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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 Statistical Analysis - Summaries of theory and Exercises solved

Applied Multivariate Statistical Analysis - Summaries of theory and Exercises solved

  • Author: Mercedes Orús Lacort
  • Publisher: Lulu.com
  • ISBN: 1291886109
  • Category: Technology & Engineering
  • Page: 124
  • View: 9392
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Applied Multivariate Statistical Analysis, is a book that is intended for university students of any college. You'll find theory as summaries, and exercises solved, on the following topics: Multiple Linear Regression, Principal Component Analysis (without and with Varimax rotation), Analysis of Hierarchical Cluster, Discriminant Analysis, and Single and Multiple Correspondence Analysis. The Minitab Statistical package, have been used in the resolution of problems.

Wahrscheinlichkeitstheorie und Stochastische Prozesse

Wahrscheinlichkeitstheorie und Stochastische Prozesse

  • Author: Michael Mürmann
  • Publisher: Springer-Verlag
  • ISBN: 364238160X
  • Category: Mathematics
  • Page: 428
  • View: 834
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Dieses Lehrbuch beschäftigt sich mit den zentralen Gebieten einer maßtheoretisch orientierten Wahrscheinlichkeitstheorie im Umfang einer zweisemestrigen Vorlesung. Nach den Grundlagen werden Grenzwertsätze und schwache Konvergenz behandelt. Es folgt die Darstellung und Betrachtung der stochastischen Abhängigkeit durch die bedingte Erwartung, die mit der Radon-Nikodym-Ableitung realisiert wird. Sie wird angewandt auf die Theorie der stochastischen Prozesse, die nach der allgemeinen Konstruktion aus der Untersuchung von Martingalen und Markov-Prozessen besteht. Neu in einem Lehrbuch über allgemeine Wahrscheinlichkeitstheorie ist eine Einführung in die stochastische Analysis von Semimartingalen auf der Grundlage einer geeigneten Stetigkeitsbedingung mit Anwendungen auf die Theorie der Finanzmärkte. Das Buch enthält zahlreiche Übungen, teilweise mit Lösungen. Neben der Theorie vertiefen Anmerkungen, besonders zu mathematischen Modellen für Phänomene der Realität, das Verständnis.​

Applied Multivariate Statistical Concepts

Applied Multivariate Statistical Concepts

  • Author: Debbie L. Hahs-Vaughn
  • Publisher: Taylor & Francis
  • ISBN: 1317811372
  • Category: Psychology
  • Page: 648
  • View: 1601
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More comprehensive than other texts, this new book covers the classic and cutting edge multivariate techniques used in today’s research. Ideal for courses on multivariate statistics/analysis/design, advanced statistics or quantitative techniques taught in psychology, education, sociology, and business, the book also appeals to researchers with no training in multivariate methods. Through clear writing and engaging pedagogy and examples using real data, Hahs-Vaughn walks students through the most used methods to learn why and how to apply each technique. A conceptual approach with a higher than usual text-to-formula ratio helps reader’s master key concepts so they can implement and interpret results generated by today’s sophisticated software. Annotated screenshots from SPSS and other packages are integrated throughout. Designed for course flexibility, after the first 4 chapters, instructors can use chapters in any sequence or combination to fit the needs of their students. Each chapter includes a ‘mathematical snapshot’ that highlights the technical components of each procedure, so only the most crucial equations are included. Highlights include: -Outlines, key concepts, and vignettes related to key concepts preview what’s to come in each chapter -Examples using real data from education, psychology, and other social sciences illustrate key concepts -Extensive coverage of assumptions including tables, the effects of their violation, and how to test for each technique -Conceptual, computational, and interpretative problems mirror the real-world problems students encounter in their studies and careers -A focus on data screening and power analysis with attention on the special needs of each particular method -Instructions for using SPSS via screenshots and annotated output along with HLM, Mplus, LISREL, and G*Power where appropriate, to demonstrate how to interpret results -Templates for writing research questions and APA-style write-ups of results which serve as models -Propensity score analysis chapter that demonstrates the use of this increasingly popular technique -A review of matrix algebra for those who want an introduction (prerequisites include an introduction to factorial ANOVA, ANCOVA, and simple linear regression, but knowledge of matrix algebra is not assumed) -www.routledge.com/9780415842365 provides the text’s datasets preformatted for use in SPSS and other statistical packages for readers, as well as answers to all chapter problems, Power Points, and test items for instructors

Topics in Applied Multivariate Analysis

Topics in Applied Multivariate Analysis

  • Author: D. M. Hawkins
  • Publisher: Cambridge University Press
  • ISBN: 9780521243681
  • Category: Mathematics
  • Page: 362
  • View: 3330
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Multivariate methods are employed widely in the analysis of experimental data but are poorly understood by those users who are not statisticians. This is because of the wide divergence between the theory and practice of multivariate methods. This book provides concise yet thorough surveys of developments in multivariate statistical analysis and gives statistically sound coverage of the subject. The contributors are all experienced in the theory and practice of multivariate methods and their aim has been to emphasize the major features from the point of view of applicability and to indicate the limitations and conditions of the techniques. Professional statisticians wanting to improve their background in applicable methods, users of high-level statistical methods wanting to improve their background in fundamentals, and graduate students of statistics will all find this volume of value and use.

Applied Multivariate Statistics for the Social Sciences, Fifth Edition

Applied Multivariate Statistics for the Social Sciences, Fifth Edition

  • Author: James P. Stevens
  • Publisher: Routledge
  • ISBN: 1136910697
  • Category: Education
  • Page: 664
  • View: 8842
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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 Statistical Analysis (Classic Version)

Applied Multivariate Statistical Analysis (Classic Version)

  • Author: Richard A. Johnson,Dean W. Wichern
  • Publisher: Pearson
  • ISBN: 9780134995397
  • Category: Multivariate analysis
  • Page: 808
  • View: 8031
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This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price. Please visit www.pearsonhighered.com/math-classics-series for a complete list of titles. For courses in Multivariate Statistics, Marketing Research, Intermediate Business Statistics, Statistics in Education, and graduate-level courses in Experimental Design and Statistics. Appropriate for experimental scientists in a variety of disciplines, this market-leading text offers a readable introduction to the statistical analysis of multivariate observations. Its primary goal is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Ideal for a junior/senior or graduate level course that explores the statistical methods for describing and analyzing multivariate data, the text assumes two or more statistics courses as a prerequisite.

Multivariate Statistical Analysis

Multivariate Statistical Analysis

A High-Dimensional Approach

  • Author: V.I. Serdobolskii
  • Publisher: Springer Science & Business Media
  • ISBN: 9401594686
  • Category: Mathematics
  • Page: 244
  • View: 727
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Multivariate Statistical Analysis

Applied Multivariate Statistics with R

Applied Multivariate Statistics with R

  • Author: Daniel Zelterman
  • Publisher: Springer
  • ISBN: 3319140930
  • Category: Medical
  • Page: 393
  • View: 8462
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This book brings the power of multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source, shareware program R, Professor 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. Zelterman uses practical examples from diverse disciplines to welcome readers from a variety of academic specialties. Those with backgrounds in statistics will learn new methods while they review more familiar topics. Chapters include exercises, real data sets, and R implementations. The data are interesting, real-world topics, particularly from health and biology-related contexts. As an example of the approach, the text examines a sample from the Behavior Risk Factor Surveillance System, discussing both the shortcomings of the data as well as useful analyses. The text avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary.

Applied Multivariate Analysis

Applied Multivariate Analysis

  • Author: Neil H. Timm
  • Publisher: Springer Science & Business Media
  • ISBN: 0387953477
  • Category: Mathematics
  • Page: 695
  • View: 5994
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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.

Applied multivariate statistics for the social sciences

Applied multivariate statistics for the social sciences

  • Author: James Stevens
  • Publisher: Lawrence Erlbaum Assoc Inc
  • ISBN: 9780805811544
  • Category: Social Science
  • Page: 629
  • View: 8293
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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 in Geohydrology and Related Sciences

Applied Multivariate Statistics in Geohydrology and Related Sciences

  • Author: Charles E. Brown
  • Publisher: Springer Science & Business Media
  • ISBN: 3642803288
  • Category: Science
  • Page: 248
  • View: 3849
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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".

Die Regeln des Lebens

Die Regeln des Lebens

  • Author: Richard Templar
  • Publisher: books4success
  • ISBN: 3941493302
  • Category: Self-Help
  • Page: 250
  • View: 5013
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Erfolgreiches Berufsleben, glückliche Beziehung und Zeit für Interessen und Freizeit. Was wissen die Menschen, die das vereinen? Die Antwort ist einfach: Sie kennen die Regeln. Die Regeln des Lebens. Der Bestseller aus der Feder von Richard Templar listet diese Regeln auf. Sie sind einfach, klar und logisch. Man kann sie im täglichen Leben problemlos umsetzen. Und sie machen einen Schritt für Schritt immer mehr zu dem Menschen, der man schon immer gerne sein wollte. Weltweit wurden von Templars "Rules"-Serie bereits mehr als 2.000.000 Exemplare verkauft. Jetzt erscheint nach "Die Regeln des Reichtums" auch der zweite Band endlich auch auf Deutsch! "Die Regeln des Lebens" entschärfen für Sie das Minenfeld aus Zeitnot, Überarbeitung und Beziehungsfrust. Wenn Sie diese Spielregeln beherrschen, können Sie Ihrem Alltag entspannt ins Auge blicken

Applied Multivariate Statistics for the Social Sciences

Applied Multivariate Statistics for the Social Sciences

Analyses with SAS and IBM’s SPSS, Sixth Edition

  • Author: Keenan A. Pituch,James P. Stevens
  • Publisher: Routledge
  • ISBN: 1317805917
  • Category: Psychology
  • Page: 814
  • View: 866
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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.

An Introduction to Applied Multivariate Analysis

An Introduction to Applied Multivariate Analysis

  • Author: Tenko Raykov,George A. Marcoulides
  • Publisher: Routledge
  • ISBN: 1136676007
  • Category: Business & Economics
  • Page: 496
  • View: 2939
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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 between the already familiar univariate statistics and multivariate statistics are emphasized throughout. The authors examine in detail how each multivariate technique can be implemented using SPSS and SAS and Mplus in the book’s later chapters. Important assumptions are discussed along the way along with tips for how to deal with pitfalls the reader may encounter. Mathematical formulas are used only in their definitional meaning rather than as elements of formal proofs. A book specific website - www.psypress.com/applied-multivariate-analysis - provides files with all of the data used in the text so readers can replicate the results. The Appendix explains the data files and its variables. The software code (for SAS and Mplus) and the menu option selections for SPSS are also discussed in the book. The book is distinguished by its use of latent variable modeling to address multivariate questions specific to behavioral and social scientists including missing data analysis and longitudinal data modeling. Ideal for graduate and advanced undergraduate students in the behavioral, social, and educational sciences, this book will also appeal to researchers in these disciplines who have limited familiarity with multivariate statistics. Recommended prerequisites include an introductory statistics course with exposure to regression analysis and some familiarity with SPSS and SAS.

Applied Multivariate Research

Applied Multivariate Research

Design and Interpretation

  • Author: Lawrence S. Meyers,Glenn Gamst,A.J. Guarino
  • Publisher: SAGE
  • ISBN: 141298811X
  • Category: Psychology
  • Page: 1078
  • View: 7103
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This book provides full coverage of the wide range of multivariate topics that graduate students across the social and behavioral sciences encounter, using a conceptual, non-mathematical, approach. Addressing correlation, multiple regression, exploratory factor analysis, MANOVA, path analysis, and structural equation modeling, it is geared toward the needs, level of sophistication, and interest in multivariate methodology that serves students in applied programs in the social and behavioral sciences. Readers are encouraged to focus on design and interpretation rather than the intricacies of specific computations.