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Some Contributions To Multivariate Statistical Analysis
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Book Synopsis Applied Multivariate Statistical Analysis by : Wolfgang Karl Härdle
Download or read book Applied Multivariate Statistical Analysis written by Wolfgang Karl Härdle and published by Springer Nature. This book was released on with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :Parimal Mukhopadhyay Publisher :World Scientific Publishing Company ISBN 13 :9813107111 Total Pages :568 pages Book Rating :4.8/5 (131 download)
Book Synopsis Multivariate Statistical Analysis by : Parimal Mukhopadhyay
Download or read book Multivariate Statistical Analysis written by Parimal Mukhopadhyay and published by World Scientific Publishing Company. This book was released on 2008-11-25 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents a classical approach to some techniques of multivariate analysis in a simple and transparent manner. It offers clear and concise development of the concepts; interpretation of the output of the analysis; and criteria for selection of the methods, taking into account the strengths and weaknesses of each. With its roots in matrix algebra, for which a separate chapter has been added as an appendix, the book includes both data-oriented techniques and a reasonable coverage of classical methods supplemented by comments about robustness and general practical applicability. It also illustrates the methods of numerical calculations at various stages.This self-contained book is ideal as an advanced textbook for graduate students in statistics and other disciplines like social, biological and physical sciences. It will also be of benefit to professional statisticians.The author is a former Professor of the Indian Statistical Institute, India.
Book Synopsis A Primer of Multivariate Statistics by : Richard J. Harris
Download or read book A Primer of Multivariate Statistics written by Richard J. Harris and published by Psychology Press. This book was released on 2001-05-01 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing upon more than 30 years of experience in working with statistics, Dr. Richard J. Harris has updated A Primer of Multivariate Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable approaches. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis. This edition retains its conversational writing style while focusing on classical techniques. The book gives the reader a feel for why one should consider diving into more detailed treatments of computer-modeling and latent-variable techniques, such as non-recursive path analysis, confirmatory factor analysis, and hierarchical linear modeling. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis.
Book Synopsis An Introduction to Applied Multivariate Analysis with R by : Brian Everitt
Download or read book An Introduction to Applied Multivariate Analysis with R written by Brian Everitt and published by Springer Science & Business Media. This book was released on 2011-04-23 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Modern Multivariate Statistical Techniques by : Alan J. Izenman
Download or read book Modern Multivariate Statistical Techniques written by Alan J. Izenman and published by Springer Science & Business Media. This book was released on 2009-03-02 with total page 757 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data. Material such as database management systems is included that has never appeared in statistics books before.
Book Synopsis Advances in Multivariate Statistical Methods by : Ashis Sengupta
Download or read book Advances in Multivariate Statistical Methods written by Ashis Sengupta and published by World Scientific. This book was released on 2009 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Printbegrænsninger: Der kan printes 10 sider ad gangen og max. 40 sider pr. session
Book Synopsis Methodology and Applications of Statistics by : Barry C. Arnold
Download or read book Methodology and Applications of Statistics written by Barry C. Arnold and published by Springer Nature. This book was released on 2022-01-04 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dedicated to one of the most outstanding researchers in the field of statistics, this volume in honor of C.R. Rao, on the occasion of his 100th birthday, provides a bird’s-eye view of a broad spectrum of research topics, paralleling C.R. Rao’s wide-ranging research interests. The book’s contributors comprise a representative sample of the countless number of researchers whose careers have been influenced by C.R. Rao, through his work or his personal aid and advice. As such, written by experts from more than 15 countries, the book’s original and review contributions address topics including statistical inference, distribution theory, estimation theory, multivariate analysis, hypothesis testing, statistical modeling, design and sampling, shape and circular analysis, and applications. The book will appeal to statistics researchers, theoretical and applied alike, and PhD students. Happy Birthday, C.R. Rao!
Book Synopsis Multivariate Statistics: Old School by : John I. Marden
Download or read book Multivariate Statistics: Old School written by John I. Marden and published by CreateSpace. This book was released on 2015-09-14 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate Statistics: Old School is amathematical and methodological introduction to multivariate statistical analysis. It presents the basic mathematical grounding that graduate statistics students need for future research, andimportant multivariate techniques useful to statisticians in general. The material provides support forfurther study in big data and machine learning. Topics include The multivariate normal and Wishart distributions Linear models, including multivariate regression and analysis of variance, andboth-sides models (GMANOVA, repeated measures, growth curves) Linear algebra useful for multivariate statistics Covariance structures, including principal components, factor analysis, independence and conditional independence, and symmetry models Classification (linear and quadratic discrimination, trees, logistic regression) Clustering (K-means, model-based, hierarchical) Other techniques, including biplots, canonical correlations, and multidimensional scaling Most of the analyses in the book use the statistical computing environment R, for which there is an available package (msos)of multivariate routines and data sets. This text was developed over many years by the author, John Marden, while teaching in the Department of Statistics, University of Illinoisat Urbana-Champaign.
Book Synopsis Modern Statistical Methods for Spatial and Multivariate Data by : Norou Diawara
Download or read book Modern Statistical Methods for Spatial and Multivariate Data written by Norou Diawara and published by Springer. This book was released on 2019-06-29 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques. Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.
Book Synopsis Applied Multivariate Statistical Concepts by : Debbie L. Hahs-Vaughn
Download or read book Applied Multivariate Statistical Concepts written by Debbie L. Hahs-Vaughn and published by Routledge. This book was released on 2016-12-01 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Multivariate Humanities by : Pieter M. Kroonenberg
Download or read book Multivariate Humanities written by Pieter M. Kroonenberg and published by Springer Nature. This book was released on 2021-06-29 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: This case study-based textbook in multivariate analysis for advanced students in the humanities emphasizes descriptive, exploratory analyses of various types of datasets from a wide range of sub-disciplines, promoting the use of multivariate analysis and illustrating its wide applicability. Fields featured include, but are not limited to, historical agriculture, arts (music and painting), theology, and stylometrics (authorship issues). Most analyses are based on existing data, earlier analysed in published peer-reviewed papers. Four preliminary methodological and statistical chapters provide general technical background to the case studies. The multivariate statistical methods presented and illustrated include data inspection, several varieties of principal component analysis, correspondence analysis, multidimensional scaling, cluster analysis, regression analysis, discriminant analysis, and three-mode analysis. The bulk of the text is taken up by 14 case studies that lean heavily on graphical representations of statistical information such as biplots, using descriptive statistical techniques to support substantive conclusions. Each study features a description of the substantive background to the data, followed by discussion of appropriate multivariate techniques, and detailed results interpreted through graphical illustrations. Each study is concluded with a conceptual summary. Datasets in SPSS are included online.
Book Synopsis Making Sense of Multivariate Data Analysis by : John Spicer
Download or read book Making Sense of Multivariate Data Analysis written by John Spicer and published by SAGE. This book was released on 2005 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: A short introduction to the subject, this text is aimed at students & practitioners in the behavioural & social sciences. It offers a conceptual overview of the foundations of MDA & of a range of specific techniques including multiple regression, logistic regression & log-linear analysis.
Book Synopsis Functional and High-Dimensional Statistics and Related Fields by : Germán Aneiros
Download or read book Functional and High-Dimensional Statistics and Related Fields written by Germán Aneiros and published by Springer Nature. This book was released on 2020-06-19 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest research on the statistical analysis of functional, high-dimensional and other complex data, addressing methodological and computational aspects, as well as real-world applications. It covers topics like classification, confidence bands, density estimation, depth, diagnostic tests, dimension reduction, estimation on manifolds, high- and infinite-dimensional statistics, inference on functional data, networks, operatorial statistics, prediction, regression, robustness, sequential learning, small-ball probability, smoothing, spatial data, testing, and topological object data analysis, and includes applications in automobile engineering, criminology, drawing recognition, economics, environmetrics, medicine, mobile phone data, spectrometrics and urban environments. The book gathers selected, refereed contributions presented at the Fifth International Workshop on Functional and Operatorial Statistics (IWFOS) in Brno, Czech Republic. The workshop was originally to be held on June 24-26, 2020, but had to be postponed as a consequence of the COVID-19 pandemic. Initiated by the Working Group on Functional and Operatorial Statistics at the University of Toulouse in 2008, the IWFOS workshops provide a forum to discuss the latest trends and advances in functional statistics and related fields, and foster the exchange of ideas and international collaboration in the field.
Book Synopsis Statistical Analysis by : Sam Kash Kachigan
Download or read book Statistical Analysis written by Sam Kash Kachigan and published by . This book was released on 1986 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic book provides the much needed conceptual explanations of advanced computer-based multivariate data analysis techniques: correlation and regression analysis, factor analysis, discrimination analysis, cluster analysis, multi-dimensional scaling, perceptual mapping, and more. It closes the gap between spiraling technology and its intelligent application, fulfilling the potential of both.
Book Synopsis Applied Multivariate Statistics for the Social Sciences by : Keenan A. Pituch
Download or read book Applied Multivariate Statistics for the Social Sciences written by Keenan A. Pituch and published by Routledge. This book was released on 2015-12-07 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Analyzing Multivariate Data by : James M. Lattin
Download or read book Analyzing Multivariate Data written by James M. Lattin and published by Duxbury Press. This book was released on 2003 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering the latest teaching and practice of applied multivariate statistics, this text is perfect for students who need an applied introduction to the subject. Lattin, Carroll, and Green have created a text that speaks to the needs of applied students who have advanced beyond the beginning level, but are not advanced statistics majors. The text provides a three-part structure. First, the authors begin each major topic by developing students' statistical intuition through applications. Then, they providing illustrative examples for support. Finally, for those courses where it will be valuable, they describe relevant mathematical underpinnings with vectors and matrix algebra. Additionally, each chapter follows a standard format. This format begins by discussing a general set of research objectives, followed by illustrative examples of problems in different areas. Then it provides an explanation of how each method works, followed by a sample problem, application of the technique, and interpretation of results.
Book Synopsis Practical Multivariate Analysis by : Abdelmonem Afifi
Download or read book Practical Multivariate Analysis written by Abdelmonem Afifi and published by CRC Press. This book was released on 2019-10-16 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. Key Features: Provides a comprehensive, practical and accessible introduction to multivariate analysis. Keeps mathematical details to a minimum, so particularly geared toward a non-statistical audience. Includes lots of detailed worked examples, guidance on computing, and exercises. Updated with a new chapter on data visualization.