Search Results: multivariate-statistical-methods-a-primer-fourth-edition

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: 7987

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 Methods

A Primer, Third Edition

Author: Bryan F.J. Manly

Publisher: CRC Press

ISBN: 9781584884149

Category: Mathematics

Page: 224

View: 957

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.

Multivariate Statistical Methods

A Primer, Second Edition

Author: Bryan F.J. Manly

Publisher: CRC Press

ISBN: 9780412603006

Category: Mathematics

Page: 232

View: 8880

The purpose of this book is to introduce multivariate statistical methods to non-mathematicians. It is not intended to be comprehensive. Rather, the intention is to keep the details to a minimum while still conveying a good idea of what can be done. In other words, it is a book to 'get you going' in a particular area of statistical methods. This second edition has retained all of Professor Manly's crystal clear style. It is based on a course that has been taught successfully at the University of Otago for a number of years but has increased coverage on measuring distances between cases based on presence-absence data, a new selection on logistic regression, new exercises and two completely new chapters on graphical methods and ordination. The author has taken into account the major shift in the way in which computer software is used, but the emphasis is on the underlying principles rather than the use of particular programs.

A Primer of Multivariate Statistics

Author: Richard J. Harris

Publisher: Psychology Press

ISBN: 1135555362

Category: Psychology

Page: 632

View: 3493

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.

Randomization, Bootstrap and Monte Carlo Methods in Biology, Third Edition

Author: Bryan F.J. Manly

Publisher: CRC Press

ISBN: 9781584885412

Category: Mathematics

Page: 480

View: 3286

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.

Multivariable Analysis

A Practical Guide for Clinicians and Public Health Researchers

Author: Mitchell H. Katz

Publisher: Cambridge University Press

ISBN: 1139500317

Category: Medical

Page: N.A

View: 1096

Now in its third edition, this highly successful text has been fully revised and updated with expanded sections on cutting-edge techniques including Poisson regression, negative binomial regression, multinomial logistic regression and proportional odds regression. As before, it focuses on easy-to-follow explanations of complicated multivariable techniques. It is the perfect introduction for all clinical researchers. It describes how to perform and interpret multivariable analysis, using plain language rather than complex derivations and mathematical formulae. It focuses on the nuts and bolts of performing research, and prepares the reader to set up, perform and interpret multivariable models. Numerous tables, graphs and tips help to demystify the process of performing multivariable analysis. The text is illustrated with many up-to-date examples from the medical literature on how to use multivariable analysis in clinical practice and in research.

Essentials of Multivariate Data Analysis

Author: Neil H. Spencer

Publisher: CRC Press

ISBN: 1466584793

Category: Mathematics

Page: 186

View: 6011

Since most datasets contain a number of variables, multivariate methods are helpful in answering a variety of research questions. Accessible to students and researchers without a substantial background in statistics or mathematics, Essentials of Multivariate Data Analysis explains the usefulness of multivariate methods in applied research. Unlike most books on multivariate methods, this one makes straightforward analyses easy to perform for those who are unfamiliar with advanced mathematical formulae. An easily understood dataset is used throughout to illustrate the techniques. The accompanying add-in for Microsoft Excel® can be used to carry out the analyses in the text. The dataset and Excel add-in are available for download on the book’s CRC Press web page. Providing a firm foundation in the most commonly used multivariate techniques, this text helps readers choose the appropriate method, learn how to apply it, and understand how to interpret the results. It prepares them for more complex analyses using software such as Minitab®, R, SAS, SPSS, and Stata.

Methods of Multivariate Analysis

Author: Alvin C. Rencher,William F. Christensen

Publisher: John Wiley & Sons

ISBN: 1118391675

Category: Mathematics

Page: 800

View: 7357

Praise for the Second Edition "This book is a systematic, well-written, well-organized text on multivariate analysis packed with intuition and insight . . . There is much practical wisdom in this book that is hard to find elsewhere." —IIE Transactions Filled with new and timely content, Methods of Multivariate Analysis, Third Edition provides examples and exercises based on more than sixty real data sets from a wide variety of scientific fields. It takes a "methods" approach to the subject, placing an emphasis on how students and practitioners can employ multivariate analysis in real-life situations. This Third Edition continues to explore the key descriptive and inferential procedures that result from multivariate analysis. Following a brief overview of the topic, the book goes on to review the fundamentals of matrix algebra, sampling from multivariate populations, and the extension of common univariate statistical procedures (including t-tests, analysis of variance, and multiple regression) to analogous multivariate techniques that involve several dependent variables. The latter half of the book describes statistical tools that are uniquely multivariate in nature, including procedures for discriminating among groups, characterizing low-dimensional latent structure in high-dimensional data, identifying clusters in data, and graphically illustrating relationships in low-dimensional space. In addition, the authors explore a wealth of newly added topics, including: Confirmatory Factor Analysis Classification Trees Dynamic Graphics Transformations to Normality Prediction for Multivariate Multiple Regression Kronecker Products and Vec Notation New exercises have been added throughout the book, allowing readers to test their comprehension of the presented material. Detailed appendices provide partial solutions as well as supplemental tables, and an accompanying FTP site features the book's data sets and related SAS® code. Requiring only a basic background in statistics, Methods of Multivariate Analysis, Third Edition is an excellent book for courses on multivariate analysis and applied statistics at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for both statisticians and researchers across a wide variety of disciplines.

An R and S-Plus® Companion to Multivariate Analysis

Author: Brian S. Everitt

Publisher: Springer Science & Business Media

ISBN: 1846281245

Category: Mathematics

Page: 221

View: 3221

Applied statisticians often need to perform analyses of multivariate data; for these they will typically use one of the statistical software packages, S-Plus or R. This book sets out how to use these packages for these analyses in a concise and easy-to-use way, and will save users having to buy two books for the job. The author is well-known for this kind of book, and so buyers will trust that he’s got it right.

A Mathematical Primer for Social Statistics

Author: John Fox

Publisher: SAGE

ISBN: 1412960800

Category: Mathematics

Page: 170

View: 4116

Beyond the introductory level, learning and effectively using statistical methods in the social sciences requires some knowledge of mathematics. This handy volume introduces the areas of mathematics that are most important to applied social statistics.

Multivariate Statistical Analysis

A Conceptual Introduction

Author: Sam Kash Kachigan

Publisher: N.A


Category: Mathematics

Page: 303

View: 5120

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.

A Primer on Linear Models

Author: John F. Monahan

Publisher: CRC Press

ISBN: 9781420062045

Category: Mathematics

Page: 304

View: 8165

A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample theory supporting common statistical methods. With coverage steadily progressing in complexity, the text first provides examples of the general linear model, including multiple regression models, one-way ANOVA, mixed-effects models, and time series models. It then introduces the basic algebra and geometry of the linear least squares problem, before delving into estimability and the Gauss–Markov model. After presenting the statistical tools of hypothesis tests and confidence intervals, the author analyzes mixed models, such as two-way mixed ANOVA, and the multivariate linear model. The appendices review linear algebra fundamentals and results as well as Lagrange multipliers. This book enables complete comprehension of the material by taking a general, unifying approach to the theory, fundamentals, and exact results of linear models.

Introduction to Multivariate Analysis

Author: Chris Chatfield,A. Collins

Publisher: CRC Press

ISBN: 9780412160400

Category: Mathematics

Page: 248

View: 6093

Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences

Author: Brian S. Everitt

Publisher: CRC Press

ISBN: 1439807701

Category: Business & Economics

Page: 320

View: 8126

Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences shows students how to apply statistical methods to behavioral science data in a sensible manner. Assuming some familiarity with introductory statistics, the book analyzes a host of real-world data to provide useful answers to real-life issues. The author begins by exploring the types and design of behavioral studies. He also explains how models are used in the analysis of data. After describing graphical methods, such as scatterplot matrices, the text covers simple linear regression, locally weighted regression, multiple linear regression, regression diagnostics, the equivalence of regression and ANOVA, the generalized linear model, and logistic regression. The author then discusses aspects of survival analysis, linear mixed effects models for longitudinal data, and the analysis of multivariate data. He also shows how to carry out principal components, factor, and cluster analyses. The final chapter presents approaches to analyzing multivariate observations from several different populations. Through real-life applications of statistical methodology, this book elucidates the implications of behavioral science studies for statistical analysis. It equips behavioral science students with enough statistical tools to help them succeed later on in their careers. Solutions to the problems as well as all R code and data sets for the examples are available at

Statistics in Plain English

Author: Timothy C. Urdan

Publisher: Psychology Press

ISBN: 0805852417

Category: Mathematics

Page: 184

View: 6801

This book is meant to be a supplement to a more detailed statistics textbook, such as that recommended for a statistics course in the social sciences. Also, as a reference book to refresh your memory about statistical concepts.

Statistics for Environmental Science and Management

Author: Bryan F. J. Manly

Publisher: Chapman and Hall/CRC

ISBN: 9781584880295

Category: Mathematics

Page: 336

View: 2648

The use of appropriate statistical methods is essential when working with environmental data. Yet, many environmental professionals are not statisticians. A ready reference guide to the most common methods used in environmental applications, Statistics for Environmental Science and Management introduces the statistical methods most frequently used by environmental scientists, managers, and students. Using a non-mathematical approach, the author describes techniques such as: environmental monitoring, impact assessment, assessing site reclamation, censored data, and Monte Carlo risk assessment, as well as the key topics of time series and spatial data. The book shows the strengths of different types of conclusions available from statistical analyses. It contains internet sources of information that give readers access to the latest information on specific topics. The author's easy to understand style makes the subject matter accessible to anyone with a rudimentary knowledge of the basics of statistics while emphasizing how the techniques are applied in the environmental field. Clearly and copiously illustrated with line drawings and tables, Statistics for Environmental Science and Management covers all the statistical methods used with environmental applications and is suitable as a text for graduate students in the environmental science area.

Applied Regression Analysis and Other Multivariable Methods

Author: David Kleinbaum,Lawrence Kupper,Azhar Nizam,Eli Rosenberg

Publisher: Cengage Learning

ISBN: 1285051084

Category: Mathematics

Page: 1072

View: 4715

This bestseller will help you learn regression-analysis methods that you can apply to real-life problems. It highlights the role of the computer in contemporary statistics with numerous printouts and exercises that you can solve using the computer. The authors continue to emphasize model development, the intuitive logic and assumptions that underlie the techniques covered, the purposes, advantages, and disadvantages of the techniques, and valid interpretations of those techniques. Available with InfoTrac Student Collections Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Analysis of Multivariate Social Science Data, Second Edition

Author: David J. Bartholomew,Fiona Steele,Jane Galbraith,Irini Moustaki

Publisher: CRC Press

ISBN: 1584889616

Category: Mathematics

Page: 384

View: 8163

Drawing on the authors’ varied experiences working and teaching in the field, Analysis of Multivariate Social Science Data, Second Editionenables a basic understanding of how to use key multivariate methods in the social sciences. With updates in every chapter, this edition expands its topics to include regression analysis, confirmatory factor analysis, structural equation models, and multilevel models. After emphasizing the summarization of data in the first several chapters, the authors focus on regression analysis. This chapter provides a link between the two halves of the book, signaling the move from descriptive to inferential methods and from interdependence to dependence. The remainder of the text deals with model-based methods that primarily make inferences about processes that generate data. Relying heavily on numerical examples, the authors provide insight into the purpose and working of the methods as well as the interpretation of data. Many of the same examples are used throughout to illustrate connections between the methods. In most chapters, the authors present suggestions for further work that go beyond conventional exercises, encouraging readers to explore new ground in social science research. Requiring minimal mathematical and statistical knowledge, this book shows how various multivariate methods reveal different aspects of data and thus help answer substantive research questions.

Statistics in MATLAB

A Primer

Author: MoonJung Cho,Wendy L. Martinez

Publisher: CRC Press

ISBN: 1466596570

Category: Business & Economics

Page: 286

View: 1670

Fulfilling the need for a practical user’s guide, Statistics in MATLAB: A Primer provides an accessible introduction to the latest version of MATLAB® and its extensive functionality for statistics. Assuming a basic knowledge of statistics and probability as well as a fundamental understanding of linear algebra concepts, this book: Covers capabilities in the main MATLAB package, the Statistics Toolbox, and the student version of MATLAB Presents examples of how MATLAB can be used to analyze data Offers access to a companion website with data sets and additional examples Contains figures and visual aids to assist in application of the software Explains how to determine what method should be used for analysis Statistics in MATLAB: A Primer is an ideal reference for undergraduate and graduate students in engineering, mathematics, statistics, economics, biostatistics, and computer science. It is also appropriate for a diverse professional market, making it a valuable addition to the libraries of researchers in statistics, computer science, data mining, machine learning, image analysis, signal processing, and engineering.

The Little SAS Book

A Primer, Fifth Edition

Author: Lora D. Delwiche,Susan J. Slaughter

Publisher: SAS Institute

ISBN: 1612904009

Category: Computers

Page: 376

View: 8551

A classic that just keeps getting better, The Little SAS Book is essential for anyone learning SAS programming. Lora Delwiche and Susan Slaughter offer a user-friendly approach so readers can quickly and easily learn the most commonly used features of the SAS language. Each topic is presented in a self-contained two-page layout complete with examples and graphics. The fifth edition has been completely updated to reflect the new default output introduced with SAS 9.3. In addition, there is a now a full chapter devoted to ODS Graphics including the SGPLOT and SGPANEL procedures. Other changes include expanded coverage of linguistic sorting and a new section on concatenating macro variables with other text. This book is a great tool for users of SAS 9.4 as well. This title belongs on every SAS programmer's bookshelf. It's a resource not just to get you started, but one you'll return to as you continue to improve your programming skills. This book is part of the SAS Press program.

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