Multivariate Statistical Methods

Author: Bryan F.J. Manly
Publisher: CRC Press
ISBN: 9781584884149
Format: PDF, ePub
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Multivariate methods are now widely used in the quantitative sciences as well as in statistics because of the ready availability of computer packages for performing the calculations. While access to suitable computer software is essential to using multivariate methods, using the software still requires a working knowledge of these methods and how they can be used. Multivariate Statistical Methods: A Primer, Third Edition introduces these methods and provides a general overview of the techniques without overwhelming you with comprehensive details. This thoroughly revised, updated edition of a best-selling introductory text retains the author's trademark clear, concise style but includes a range of new material, new exercises, and supporting materials on the Web. New in the Third Edition: Fully updated references Additional examples and exercises from the social and environmental sciences A comparison of the various statistical software packages, including Stata, Statistica, SAS Minitab, and Genstat, particularly in terms of their ease of use by beginners In his efforts to produce a book that is as short as possible and that enables you to begin to use multivariate methods in an intelligent manner, the author has produced a succinct and handy reference. With updated information on multivariate analyses, new examples using the latest software, and updated references, this book provides a timely introduction to useful tools for statistical analysis.

An Introduction to Statistical Concepts

Author: Debbie L Hahs-Vaughn
Publisher: Routledge
ISBN: 1136490124
Format: PDF, Kindle
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This comprehensive, flexible text is used in both one- and two-semester courses to review introductory through intermediate statistics. Instructors select the topics that are most appropriate for their course. Its conceptual approach helps students more easily understand the concepts and interpret SPSS and research results. Key concepts are simply stated and occasionally reintroduced and related to one another for reinforcement. Numerous examples demonstrate their relevance. This edition features more explanation to increase understanding of the concepts. Only crucial equations are included. In addition to updating throughout, the new edition features: New co-author, Debbie L. Hahs-Vaughn, the 2007 recipient of the University of Central Florida's College of Education Excellence in Graduate Teaching Award. A new chapter on logistic regression models for today's more complex methodologies. More on computing confidence intervals and conducting power analyses using G*Power. Many more SPSS screenshots to assist with understanding how to navigate SPSS and annotated SPSS output to assist in the interpretation of results. Extended sections on how to write-up statistical results in APA format. New learning tools including chapter-opening vignettes, outlines, and a list of key concepts, many more examples, tables, and figures, boxes, and chapter summaries. More tables of assumptions and the effects of their violation including how to test them in SPSS. 33% new conceptual, computational, and all new interpretative problems. A website that features PowerPoint slides, answers to the even-numbered problems, and test items for instructors, and for students the chapter outlines, key concepts, and datasets that can be used in SPSS and other packages, and more. Each chapter begins with an outline, a list of key concepts, and a vignette related to those concepts. Realistic examples from education and the behavioral sciences illustrate those concepts. Each example examines the procedures and assumptions and provides instructions for how to run SPSS, including annotated output, and tips to develop an APA style write-up. Useful tables of assumptions and the effects of their violation are included, along with how to test assumptions in SPSS. 'Stop and Think' boxes provide helpful tips for better understanding the concepts. Each chapter includes computational, conceptual, and interpretive problems. The data sets used in the examples and problems are provided on the web. Answers to the odd-numbered problems are given in the book. The first five chapters review descriptive statistics including ways of representing data graphically, statistical measures, the normal distribution, and probability and sampling. The remainder of the text covers inferential statistics involving means, proportions, variances, and correlations, basic and advanced analysis of variance and regression models. Topics not dealt with in other texts such as robust methods, multiple comparison and nonparametric procedures, and advanced ANOVA and multiple and logistic regression models are also reviewed. Intended for one- or two-semester courses in statistics taught in education and/or the behavioral sciences at the graduate and/or advanced undergraduate level, knowledge of statistics is not a prerequisite. A rudimentary knowledge of algebra is required.

A primer of multivariate statistics

Author: Richard J. Harris
Publisher:
ISBN:
Format: PDF, ePub
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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.

Multivariate Statistics

Author: Yasunori Fujikoshi
Publisher: John Wiley & Sons
ISBN: 0470411694
Format: PDF, ePub, Mobi
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A comprehensive examination of high-dimensional analysis ofmultivariate methods and their real-world applications Multivariate Statistics: High-Dimensional and Large-SampleApproximations is the first book of its kind to explore howclassical multivariate methods can be revised and used in place ofconventional statistical tools. Written by prominent researchers inthe field, the book focuses on high-dimensional and large-scaleapproximations and details the many basic multivariate methods usedto achieve high levels of accuracy. The authors begin with a fundamental presentation of the basictools and exact distributional results of multivariate statistics,and, in addition, the derivations of most distributional resultsare provided. Statistical methods for high-dimensional data, suchas curve data, spectra, images, and DNA microarrays, are discussed.Bootstrap approximations from a methodological point of view,theoretical accuracies in MANOVA tests, and model selectioncriteria are also presented. Subsequent chapters feature additionaltopical coverage including: High-dimensional approximations of various statistics High-dimensional statistical methods Approximations with computable error bound Selection of variables based on model selection approach Statistics with error bounds and their appearance indiscriminant analysis, growth curve models, generalized linearmodels, profile analysis, and multiple comparison Each chapter provides real-world applications and thoroughanalyses of the real data. In addition, approximation formulasfound throughout the book are a useful tool for both practical andtheoretical statisticians, and basic results on exact distributionsin multivariate analysis are included in a comprehensive, yetaccessible, format. Multivariate Statistics is an excellent book for courseson probability theory in statistics at the graduate level. It isalso an essential reference for both practical and theoreticalstatisticians who are interested in multivariate analysis and whowould benefit from learning the applications of analyticalprobabilistic methods in statistics.

Nonparametric Statistical Methods

Author: Myles Hollander
Publisher: John Wiley & Sons
ISBN: 1118553292
Format: PDF, Kindle
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Praise for the Second Edition “This book should be an essential part of the personallibrary of every practicingstatistician.”—Technometrics Thoroughly revised and updated, the new edition of NonparametricStatistical Methods includes additional modern topics andprocedures, more practical data sets, and new problems fromreal-life situations. The book continues to emphasize theimportance of nonparametric methods as a significant branch ofmodern statistics and equips readers with the conceptual andtechnical skills necessary to select and apply the appropriateprocedures for any given situation. Written by leading statisticians, Nonparametric StatisticalMethods, Third Edition provides readers with crucialnonparametric techniques in a variety of settings, emphasizing theassumptions underlying the methods. The book provides an extensivearray of examples that clearly illustrate how to use nonparametricapproaches for handling one- or two-sample location and dispersionproblems, dichotomous data, and one-way and two-way layoutproblems. In addition, the Third Edition features: The use of the freely available R software to aid incomputation and simulation, including many new R programs writtenexplicitly for this new edition New chapters that address density estimation, wavelets,smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science,astronomy, biology, criminology, education, engineering,environmental science, geology, home economics, medicine,oceanography, physics, psychology, sociology, and spacescience Nonparametric Statistical Methods, Third Edition is anexcellent reference for applied statisticians and practitioners whoseek a review of nonparametric methods and their relevantapplications. The book is also an ideal textbook forupper-undergraduate and first-year graduate courses in appliednonparametric statistics.

A Primer on Experiments with Mixtures

Author: John A. Cornell
Publisher: John Wiley & Sons
ISBN: 0470907428
Format: PDF, Docs
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The concise yet authoritative presentation of key techniques for basic mixtures experiments Inspired by the author's bestselling advanced book on the topic, A Primer on Experiments with Mixtures provides an introductory presentation of the key principles behind experimenting with mixtures. Outlining useful techniques through an applied approach with examples from real research situations, the book supplies a comprehensive discussion of how to design and set up basic mixture experiments, then analyze the data and draw inferences from results. Drawing from his extensive experience teaching the topic at various levels, the author presents the mixture experiments in an easy-to-follow manner that is void of unnecessary formulas and theory. Succinct presentations explore key methods and techniques for carrying out basic mixture experiments, including: Designs and models for exploring the entire simplex factor space, with coverage of simplex-lattice and simplex-centroid designs, canonical polynomials, the plotting of individual residuals, and axial designs Multiple constraints on the component proportions in the form of lower and/or upper bounds, introducing L-Pseudocomponents, multicomponent constraints, and multiple lattice designs for major and minor component classifications Techniques for analyzing mixture data such as model reduction and screening components, as well as additional topics such as measuring the leverage of certain design points Models containing ratios of the components, Cox's mixture polynomials, and the fitting of a slack variable model A review of least squares and the analysis of variance for fitting data Each chapter concludes with a summary and appendices with details on the technical aspects of the material. Throughout the book, exercise sets with selected answers allow readers to test their comprehension of the material, and References and Recommended Reading sections outline further resources for study of the presented topics. A Primer on Experiments with Mixtures is an excellent book for one-semester courses on mixture designs and can also serve as a supplement for design of experiments courses at the upper-undergraduate and graduate levels. It is also a suitable reference for practitioners and researchers who have an interest in experiments with mixtures and would like to learn more about the related mixture designs and models.

Mathematics of Chance

Author: Jirí Andel
Publisher: John Wiley & Sons
ISBN: 0470317914
Format: PDF, Mobi
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Mathematics of Chance utilizes simple, real-world problems-some of which have only recently been solved-to explain fundamental probability theorems, methods, and statistical reasoning. Jiri Andel begins with a basic introduction to probability theory and its important points before moving on to more specific sections on vital aspects of probability, using both classic and modern problems. Each chapter begins with easy, realistic examples before covering the general formulations and mathematical treatments used. The reader will find ample use for a chapter devoted to matrix games and problem sets concerning waiting, probability calculations, expectation calculations, and statistical methods. A special chapter utilizes problems that relate to areas of mathematics outside of statistics and considers certain mathematical concepts from a probabilistic point of view. Sections and problems cover topics including: * Random walks * Principle of reflection * Probabilistic aspects of records * Geometric distribution * Optimization * The LAD method, and more Knowledge of the basic elements of calculus will be sufficient in understanding most of the material presented here, and little knowledge of pure statistics is required. Jiri Andel has produced a compact reference for applied statisticians working in industry and the social and technical sciences, and a book that suits the needs of students seeking a fundamental understanding of probability theory.

The Fitness of Information

Author: Chaomei Chen
Publisher: John Wiley & Sons
ISBN: 1118594207
Format: PDF, Mobi
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Theories and practices to assess critical information in acomplex adaptive system Organized for readers to follow along easily, The Fitness ofInformation: Quantitative Assessments of Critical Evidenceprovides a structured outline of the key challenges in assessingcrucial information in a complex adaptive system. Illustrating avariety of computational and explanatory challenges, the bookdemonstrates principles and practical implications of exploring andassessing the fitness of information in an extensible framework ofadaptive landscapes. The book’s first three chapters introduce fundamentalprinciples and practical examples in connection to the nature ofaesthetics, mental models, and the subjectivity of evidence. Inparticular, the underlying question is how these issues can beaddressed quantitatively, not only computationally but alsoexplanatorily. The next chapter illustrates how one can reduce thelevel of complexity in understanding the structure and dynamics ofscientific knowledge through the design and use of the CiteSpacesystem for visualizing and analyzing emerging trends in scientificliterature. The following two chapters explain the concepts ofstructural variation and the fitness of information in a frameworkthat builds on the idea of fitness landscape originally introducedto study population evolution. The final chapter presents adual-map overlay technique and demonstrates how it supports avariety of analytic tasks for a new type of portfolioanalysis. The Fitness of Information: Quantitative Assessments of CriticalEvidence also features: In-depth case studies and examples that characterizefar-reaching concepts, illustrate underlying principles, anddemonstrate profound challenges and complexities at various levelsof analytic reasoning Wide-ranging topics that underline the common theme, from thesubjectivity of evidence in criminal trials to detecting earlysigns of critical transitions and mechanisms behind radicalpatents An extensible and unifying framework for visual analytics bytransforming analytic reasoning tasks to the assessment of criticalevidence The Fitness of Information: Quantitative Assessments of CriticalEvidence is a suitable reference for researchers, analysts, andpractitioners who are interested in analyzing evidence and makingdecisions with incomplete, uncertain, and even conflictinginformation. The book is also an excellent textbook forupper-undergraduate and graduate-level courses on visual analytics,information visualization, and business analytics and decisionsupport systems.

Randomization Bootstrap and Monte Carlo Methods in Biology Third Edition

Author: Bryan F.J. Manly
Publisher: CRC Press
ISBN: 9781584885412
Format: PDF, ePub, Docs
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Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. This new edition of the bestselling Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates the value of a number of these methods with an emphasis on biological applications. This textbook focuses on three related areas in computational statistics: randomization, bootstrapping, and Monte Carlo methods of inference. The author emphasizes the sampling approach within randomization testing and confidence intervals. Similar to randomization, the book shows how bootstrapping, or resampling, can be used for confidence intervals and tests of significance. It also explores how to use Monte Carlo methods to test hypotheses and construct confidence intervals. New to the Third Edition Updated information on regression and time series analysis, multivariate methods, survival and growth data as well as software for computational statistics References that reflect recent developments in methodology and computing techniques Additional references on new applications of computer-intensive methods in biology Providing comprehensive coverage of computer-intensive applications while also offering data sets online, Randomization, Bootstrap and Monte Carlo Methods in Biology, Third Edition supplies a solid foundation for the ever-expanding field of statistics and quantitative analysis in biology.