Advanced and Multivariate Statistical Methods

Practical Application and Interpretation
Author: Craig A. Mertler,Rachel Vannatta Reinhart
Publisher: Routledge
ISBN: 1351971662
Category: Psychology
Page: 390
View: 5985

Continue Reading →

Ideal for non-math majors, Advanced and Multivariate Statistical Methods teaches students to interpret, present, and write up results for each statistical technique without overemphasizing advanced math. This highly applied approach covers the why, what, when and how of advanced and multivariate statistics in a way that is neither too technical nor too mathematical. Students also learn how to compute each technique using SPSS software. New to the Sixth Edition Instructor ancillaries are now available with the sixth edition. All SPSS directions and screenshots have been updated to Version 23 of the software. Student learning objectives have been added as a means for students to target their learning and for instructors to focus their instruction. Key words are reviewed and reinforced in the end of chapter material to ensure that students understand the vocabulary of advanced and multivariate statistics.

Understanding Advanced Statistical Methods


Author: Peter Westfall,Kevin S. S. Henning
Publisher: CRC Press
ISBN: 1466512105
Category: Mathematics
Page: 569
View: 3629

Continue Reading →

Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum likelihood, bootstrapping, nonparametrics, and Bayesian methods. The book teaches students how to properly model, think critically, and design their own studies to avoid common errors. It leads them to think differently not only about math and statistics but also about general research and the scientific method. With a focus on statistical models as producers of data, the book enables students to more easily understand the machinery of advanced statistics. It also downplays the "population" interpretation of statistical models and presents Bayesian methods before frequentist ones. Requiring no prior calculus experience, the text employs a "just-in-time" approach that introduces mathematical topics, including calculus, where needed. Formulas throughout the text are used to explain why calculus and probability are essential in statistical modeling. The authors also intuitively explain the theory and logic behind real data analysis, incorporating a range of application examples from the social, economic, biological, medical, physical, and engineering sciences. Enabling your students to answer the why behind statistical methods, this text teaches them how to successfully draw conclusions when the premises are flawed. It empowers them to use advanced statistical methods with confidence and develop their own statistical recipes. Ancillary materials are available on the book’s website.

Understanding and Using Advanced Statistics

A Practical Guide for Students
Author: Jeremy J Foster,Emma Barkus,Christian Yavorsky
Publisher: SAGE
ISBN: 9781412900140
Category: Mathematics
Page: 178
View: 6249

Continue Reading →

The spread of sophisticated computer packages and the machinery on which to run them has meant that procedures which were previously only available to experienced researchers with access to expensive machines and research students can now be carried out in a few seconds by almost every undergraduate. Understanding and Using Advanced Statistics provides the basis for gaining an understanding of what these analytic procedures do, when they should be used, and what the results provided signify. This comprehensive textbook guides students and researchers through the transition from simple statistics to more complex procedures with accessible language and illustration.

Advanced Statistical Methods for the Analysis of Large Data-Sets


Author: Agostino Di Ciaccio,Mauro Coli,Jose Miguel Angulo Ibanez
Publisher: Springer Science & Business Media
ISBN: 3642210368
Category: Mathematics
Page: 486
View: 1991

Continue Reading →

The theme of the meeting was “Statistical Methods for the Analysis of Large Data-Sets”. In recent years there has been increasing interest in this subject; in fact a huge quantity of information is often available but standard statistical techniques are usually not well suited to managing this kind of data. The conference serves as an important meeting point for European researchers working on this topic and a number of European statistical societies participated in the organization of the event. The book includes 45 papers from a selection of the 156 papers accepted for presentation and discussed at the conference on “Advanced Statistical Methods for the Analysis of Large Data-sets.”

Applied Multivariate Statistical Concepts


Author: Debbie L. Hahs-Vaughn
Publisher: Routledge
ISBN: 1317811364
Category: Psychology
Page: 662
View: 9175

Continue Reading →

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 ?

Applied Multivariate Research

Design and Interpretation
Author: Lawrence S. Meyers,Glenn Gamst,A.J. Guarino
Publisher: SAGE Publications
ISBN: 1506329780
Category: Social Science
Page: 1016
View: 8897

Continue Reading →

Using a conceptual, non-mathematical approach, the updated Third Edition of Applied Multivariate Research: Design and Interpretation 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.

Multivariate Statistical Methods

A Primer, Fourth Edition
Author: Bryan F.J. Manly,Jorge A. Navarro Alberto
Publisher: CRC Press
ISBN: 1498728995
Category: Mathematics
Page: 269
View: 3847

Continue Reading →

Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.

Multivariate Statistical Process Control with Industrial Applications


Author: Robert L. Mason,John C. Young
Publisher: SIAM
ISBN: 0898714966
Category: Technology & Engineering
Page: 263
View: 6641

Continue Reading →

Detailed coverage of the practical aspects of multivariate statistical process control (MVSPC) based on the application of Hotelling's T2 statistic. MVSPC is the application of multivariate statistical techniques to improve the quality and productivity of an industrial process. Provides valuable insight into the T2 statistic.

How to Use SPSS®

A Step-By-Step Guide to Analysis and Interpretation
Author: Brian C. Cronk
Publisher: Routledge
ISBN: 1351390007
Category: Psychology
Page: 166
View: 8821

Continue Reading →

How to Use SPSS® is designed with the novice computer user in mind and for people who have no previous experience of using SPSS. Each chapter is divided into short sections that describe the statistic being used, important underlying assumptions, and how to interpret the results and express them in a research report. The book begins with the basics, such as starting SPSS, defining variables, and entering and saving data. It covers all major statistical techniques typically taught in beginning statistics classes, such as descriptive statistics, graphing data, prediction and association, parametric inferential statistics, nonparametric inferential statistics and statistics for test construction. More than 250 screenshots (including sample output) throughout the book show students exactly what to expect as they follow along using SPSS. The book includes a glossary of statistical terms and practice exercises. A complete set of online resources including video tutorials and output files for students, and PowerPoint slides and test bank questions for instructors, make How to Use SPSS® the definitive, field-tested resource for learning SPSS. New to this edition: Fully updated to SPSS 24 and IBM SPSS Statistics Cloud New chapter on ANOVA New material on inter-rater reliability New material on syntax Additional coverage of data entry and management

Handbook of Applied Multivariate Statistics and Mathematical Modeling


Author: Howard E.A. Tinsley,Steven D. Brown
Publisher: Academic Press
ISBN: 9780080533568
Category: Mathematics
Page: 721
View: 7443

Continue Reading →

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

Analyses with SAS and IBM’s SPSS, Sixth Edition
Author: Keenan A. Pituch,James P. Stevens
Publisher: Routledge
ISBN: 1317805925
Category: Psychology
Page: 794
View: 9021

Continue Reading →

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.

Advanced Statistics for Kinesiology and Exercise Science

A Practical Guide to ANOVA and Regression Analyses
Author: Moh H. Malek,Jared W. Coburn,William D. Marelich
Publisher: Routledge
ISBN: 1351864564
Category: Sports & Recreation
Page: 138
View: 9618

Continue Reading →

Advanced Statistics for Kinesiology and Exercise Science is the first textbook to cover advanced statistical methods in the context of the study of human performance. Divided into three distinct sections, the book introduces and explores in depth both analysis of variance (ANOVA) and regressions analyses, including chapters on: preparing data for analysis; one-way, factorial, and repeated-measures ANOVA; analysis of covariance and multiple analyses of variance and covariance; diagnostic tests; regression models for quantitative and qualitative data; model selection and validation; logistic regression Drawing clear lines between the use of IBM SPSS Statistics software and interpreting and analyzing results, and illustrated with sport and exercise science-specific sample data and results sections throughout, the book offers an unparalleled level of detail in explaining advanced statistical techniques to kinesiology students. Advanced Statistics for Kinesiology and Exercise Science is an essential text for any student studying advanced statistics or research methods as part of an undergraduate or postgraduate degree programme in kinesiology, sport and exercise science, or health science.

Advanced Statistics in Research

Reading, Understanding, and Writing Up Data Analysis Results
Author: Larry Hatcher
Publisher: Shadow Finch Media LLC
ISBN: 9780985867003
Category: Mathematical statistics
Page: 632
View: 9147

Continue Reading →

"Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results" is the simple, nontechnical introduction to the most complex multivariate statistics presented in empirical research articles. "wwwStatsInResearch.com, " is a companion website that provides free sample chapters, exercises, and PowerPoint slides for students and teachers. A free 600-item test bank is available to instructors. "Advanced Statistics in Research" does not show how to "perform" statistical procedures--it shows how to read, understand, and interpret them, as they are typically presented in journal articles and research reports. It demystifies the sophisticated statistics that stop most readers cold: multiple regression, logistic regression, discriminant analysis, ANOVA, ANCOVA, MANOVA, factor analysis, path analysis, structural equation modeling, meta-analysis--and more. "Advanced Statistics in Research" assumes that you have never had a course in statistics. It begins at the beginning, with research design, central tendency, variability, z scores, and the normal curve. You will learn (or re-learn) the big-three results that are common to most procedures: statistical significance, confidence intervals, and effect size. Step-by-step, each chapter gently builds on earlier concepts. Matrix algebra is avoided, and complex topics are explained using simple, easy-to-understand examples. "Need help writing up your results?" Advanced Statistics in Research shows how data-analysis results can be summarized in text, tables, and figures according to APA format. You will see how to present the basics (e.g., means and standard deviations) as well as the advanced (e.g., factor patterns, post-hoc tests, path models, and more). "Advanced Statistics in Research" is appropriate as a textbook for graduate students and upper-level undergraduates (see supplementary materials at StatsInResearch.com). It also serves as a handy shelf reference for investigators and all consumers of research.

Human Resource Management

Strategic and International Perspectives
Author: Jonathan Crawshaw,Pawan Budhwar,Professor of International Human Resource Management Pawan Budhwar,Ann Davis
Publisher: SAGE
ISBN: 1526412705
Category: Business & Economics
Page: 496
View: 5203

Continue Reading →

A comprehensive introduction to HRM for students who are new to the field, but who will be seeking employment in a global market, working with diverse colleagues and across international borders. Broken down into three parts covering Strategic Issues in HRM, HRM in Practice and HRM in Context, and weaving international and cross-cultural perspectives throughout, the text explores the ever-changing world of human resource management. The various theories, practices and debates that populate this field are examined, and the challenges and controversies that arise when theory meets practice are explored. The international dimension in all its aspects including cross-cultural working, diversity, equality and international business have been considered throughout. Practical learning features have been included to help students develop skills they can apply to their course and in graduate employment. In the new edition, the authors have further explored the international context for HRM, not just for multinational corporations but also for small businesses and not-for-profit organizations, with added analysis on the importance of recognizing that effective functioning of organizations is not simply measured by financial performance, but also by taking into account the broader social, economic and political contexts. International case studies covering emerging economies and specific ethical issues are included with each chapter containing two case studies - one short case mid-chapter and a longer end-of-chapter case, each of which has a set of accompanying questions for students to explore individually or in groups to broaden their learning. The book is supported by a SAGE Edge site, featuring a range of tools and resources for lecturers and students, including SAGE journal articles, PowerPoint slides, web and video links, interactive multiple choice questions, chapter specific podcasts and an instructor’s manual. Suitable for undergraduates and post-graduate students looking for a strategic and international perspective of HRM.

Multiparametric Statistics


Author: Vadim Ivanovich Serdobolskii
Publisher: Elsevier
ISBN: 9780080555928
Category: Mathematics
Page: 334
View: 2421

Continue Reading →

This monograph presents mathematical theory of statistical models described by the essentially large number of unknown parameters, comparable with sample size but can also be much larger. In this meaning, the proposed theory can be called "essentially multiparametric". It is developed on the basis of the Kolmogorov asymptotic approach in which sample size increases along with the number of unknown parameters. This theory opens a way for solution of central problems of multivariate statistics, which up until now have not been solved. Traditional statistical methods based on the idea of an infinite sampling often break down in the solution of real problems, and, dependent on data, can be inefficient, unstable and even not applicable. In this situation, practical statisticians are forced to use various heuristic methods in the hope the will find a satisfactory solution. Mathematical theory developed in this book presents a regular technique for implementing new, more efficient versions of statistical procedures. Near exact solutions are constructed for a number of concrete multi-dimensional problems: estimation of expectation vectors, regression and discriminant analysis, and for the solution to large systems of empiric linear algebraic equations. It is remarkable that these solutions prove to be not only non-degenerating and always stable, but also near exact within a wide class of populations. In the conventional situation of small dimension and large sample size these new solutions far surpass the classical, commonly used consistent ones. It can be expected in the near future, for the most part, traditional multivariate statistical software will be replaced by the always reliable and more efficient versions of statistical procedures implemented by the technology described in this book. This monograph will be of interest to a variety of specialists working with the theory of statistical methods and its applications. Mathematicians would find new classes of urgent problems to be solved in their own regions. Specialists in applied statistics creating statistical packages will be interested in more efficient methods proposed in the book. Advantages of these methods are obvious: the user is liberated from the permanent uncertainty of possible instability and inefficiency and gets algorithms with unimprovable accuracy and guaranteed for a wide class of distributions. A large community of specialists applying statistical methods to real data will find a number of always stable highly accurate versions of algorithms that will help them to better solve their scientific or economic problems. Students and postgraduates will be interested in this book as it will help them get at the foremost frontier of modern statistical science. - Presents original mathematical investigations and open a new branch of mathematical statistics - Illustrates a technique for developing always stable and efficient versions of multivariate statistical analysis for large-dimensional problems - Describes the most popular methods some near exact solutions; including algorithms of non-degenerating large-dimensional discriminant and regression analysis

Aviation Systems

Management of the Integrated Aviation Value Chain
Author: Andreas Wittmer,Thomas Bieger,Roland Müller
Publisher: Springer Science & Business Media
ISBN: 9783642200809
Category: Business & Economics
Page: 238
View: 1650

Continue Reading →

This book aims to provide comprehensive coverage of the field of air transportation, giving attention to all major aspects, such as aviation regulation, economics, management and strategy. The book approaches aviation as an interrelated economic system and in so doing presents the “big picture” of aviation in the market economy. It explains the linkages between domains such as politics, society, technology, economy, ecology, regulation and how these influence each other. Examples of airports and airlines, and case studies in each chapter support the application-oriented approach. Students and researchers in business administration with a focus on the aviation industry, as well as professionals in the industry looking to refresh or broaden their knowledge of the field will benefit from this book.

Higher-Order Growth Curves and Mixture Modeling with Mplus

A Practical Guide
Author: Kandauda K.A.S. Wickrama,Tae Kyoung Lee,Catherine Walker O’Neal,Frederick O. Lorenz
Publisher: Routledge
ISBN: 1317283937
Category: Psychology
Page: 326
View: 2671

Continue Reading →

This practical introduction to second-order and growth mixture models using Mplus introduces simple and complex techniques through incremental steps. The authors extend latent growth curves to second-order growth curve and mixture models and then combine the two. To maximize understanding, each model is presented with basic structural equations, figures with associated syntax that highlight what the statistics mean, Mplus applications, and an interpretation of results. Examples from a variety of disciplines demonstrate the use of the models and exercises allow readers to test their understanding of the techniques. A comprehensive introduction to confirmatory factor analysis, latent growth curve modeling, and growth mixture modeling is provided so the book can be used by readers of various skill levels. The book’s datasets are available on the web. Highlights include: -Illustrative examples using Mplus 7.4 include conceptual figures, Mplus program syntax, and an interpretation of results to show readers how to carry out the analyses with actual data. -Exercises with an answer key allow readers to practice the skills they learn. -Applications to a variety of disciplines appeal to those in the behavioral, social, political, educational, occupational, business, and health sciences. -Data files for all the illustrative examples and exercises at www.routledge.com/9781138925151 allow readers to test their understanding of the concepts. -Point to Remember boxes aid in reader comprehension or provide in-depth discussions of key statistical or theoretical concepts. Part 1 introduces basic structural equation modeling (SEM) as well as first- and second-order growth curve modeling. The book opens with the basic concepts from SEM, possible extensions of conventional growth curve models, and the data and measures used throughout the book. The subsequent chapters in part 1 explain the extensions. Chapter 2 introduces conventional modeling of multidimensional panel data, including confirmatory factor analysis (CFA) and growth curve modeling, and its limitations. The logical and theoretical extension of a CFA to a second-order growth curve, known as curve-of-factors model (CFM), are explained in Chapter 3. Chapter 4 illustrates the estimation and interpretation of unconditional and conditional CFMs. Chapter 5 presents the logical and theoretical extension of a parallel process model to a second-order growth curve, known as factor-of-curves model (FCM). Chapter 6 illustrates the estimation and interpretation of unconditional and conditional FCMs. Part 2 reviews growth mixture modeling including unconditional growth mixture modeling (Ch. 7) and conditional growth mixture models (Ch. 8). How to extend second-order growth curves (curve-of-factors and factor-of-curves models) to growth mixture models is highlighted in Chapter 9. Ideal as a supplement for use in graduate courses on (advanced) structural equation, multilevel, longitudinal, or latent variable modeling, latent growth curve and mixture modeling, factor analysis, multivariate statistics, or advanced quantitative techniques (methods) taught in psychology, human development and family studies, business, education, health, and social sciences, this book’s practical approach also appeals to researchers. Prerequisites include a basic knowledge of intermediate statistics and structural equation modeling.

Applied Multivariate Statistical Analysis


Author: Wolfgang Karl Härdle,Léopold Simar
Publisher: Springer
ISBN: 3662451719
Category: Business & Economics
Page: 580
View: 1852

Continue Reading →

Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners. All chapters include practical exercises that highlight applications in different multivariate data analysis fields. All of the examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate Statistical Analysis offers the following new features: A new chapter on Variable Selection (Lasso, SCAD and Elastic Net) All exercises are supplemented by R and MATLAB code that can be found on www.quantlet.de. The practical exercises include solutions that can be found in Härdle, W. and Hlavka, Z., Multivariate Statistics: Exercises and Solutions. Springer Verlag, Heidelberg.