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Using Multivariate Statistics
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Barbara G Tabachnick, Linda S Fidell
This text takes a practical approach to multivariate data analysis, with an introduction to the most commonly encountered statistical and multivariate techniques. Using Multivariate Statistics provides practical guidelines for conducting numerous types of multivariate statistical analyses. It gives syntax and output for accomplishing many analyses ...
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An Introduction to Categorical Data Analysis
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Alan Agresti
Praise for the First Edition: 'This is a superb text from which to teach categorical data analysis, at a variety of levels...[t]his book can be very highly recommended' - "Short Book Reviews". 'Of great interest to potential readers is the variety of fields that are represented in the examples: health care, financial, government, product marketing ...
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Applied Multivariate Statistical Analysis
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Richard A Johnson, Dean W Wichern
For courses in Multivariate Statistics, Marketing Research, Intermediate Business Statistics, Statistics in Education, and graduate-level courses in Experimental Design and Statistics. Appropriate for experimental scientists in a variety of disciplines, this market-leading text offers a readable introduction to the statistical analysis of ...
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Introduction to Multivariate Statistical Analysis
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T W Anderson
Multivariate Statistical Simulation Mark E. Johnson For the researcher in statistics, probability, and operations research involved in the design and execution of a computer-aided simulation study utilizing continuous multivariate distributions, this book considers the properties of such distributions from a unique perspective. With enhancing ...
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Statistical Analysis: An Interdisciplinary Introduction to Univariate and Multivariate Methods
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Sam Kash Kachigan
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Reading & Understanding Multivariate Statistics
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Laurence G Grimm (Editor), Paul R Yarnold (Editor)
This text aims to help researchers and students to understand the purpose and presentation of multivariate statistical techniques. The most commonly used techniques are described in detail, such as multiple regression and correlation and path analysis
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Data Reduction and Error Analysis for the Physical Sciences
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Philip R Bevington
This book is designed as a laboratory companion, student textbook or reference book for professional scientists. The text is for use in one-term numerical analysis, data and error analysis, or computer methods courses, or for laboratory use. It is for the sophomore-junior level, and calculus is a prerequisite. The new edition includes applications ...
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Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning
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Alan Julian Izenman
Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has opened up the field of bioinformatics. These exciting developments, which led to the introduction of ...
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Categorical Data Analysis
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Alan Agresti
"Amstat News" asked three review editors to rate their top five favorite books in the September 2003 issue. "Categorical Data Analysis" was among those chosen. It is a valuable new edition of a standard reference. "A must have book for anyone expecting to do research and/or applications in categorical data analysis." - "Statistics in Medicine on ...
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Multivariate Statistical Analysis: A Conceptual Introduction
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Sam Kash Kachigan
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 ...
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Applied Statistics: From Bivariate Through Multivariate Techniques
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by
Dr. Rebecca M Warner
With an approach that does not require formal mathematics training (equations are accompanied by verbal explanations), this textbook provides a clear introduction to widely used topics in multivariate statistics, including Multiple Regression, Discriminant Analysis, MANOVA, Factor Analysis, and Binary Logistic Regression. Each chapter presents a ...
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An Introduction to Multivariate Data
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Trevor Cox, Joao Branco
Multivariate data appear in all scientific fields of investigation and the study of multivariate analysis has become central to the discipline of data science. Not only is it part of the statistical education curriculum but it is also an essential tool for applied scientists in their research work. An Introduction to Multivariate Data Analysis ...
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Multivariate data analysis
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by
Joseph F. Hair
For graduate and upper-level undergraduate marketing research courses. For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis. Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical ...
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Models for Discrete Data
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Daniel Zelterman, PH.D.
Discrete or count data arise in experiments where the outcome variables are the numbers of individuals classified into unique, non-overlapping categories. This revised edition describes the statistical models used in the analysis and summary of such data, and provides a sound introduction to the subject for graduate students and practitioners ...
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Winning at the Races: Computer Discoveries in Thoroughbred Handicapping
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William Quirin, Tom Ainslie
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Applied regression analysis and other multivariable methods
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David G. Kleinbaum, Lawrence L. Kupper
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 ...
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Multivariable Analysis: A Practical Guide for Clinicians
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Mitchell H Katz
Multivariable analysis is a challenging subject for clinicians, whether they are novice researchers or trained practitioners. Most basic biostatistics books do not cover multivariable analysis, while existing multivariable analysis books are dense with mathematical formulas. Multivariable Analysis: A Practical Guide for Clinicians steps aside ...
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Reading and Understanding More Multivariate Statistics
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Laurence G Grimm (Editor), Paul R Yarnold (Editor)
This work describes research questions for which the statistic is most appropriate, the underlying assumptions and rationale of the analysis, and the logic behind interpreting the results. It is designed to clarify each statistic's logic and utility rather than teach applications.
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Understanding Multivariate Methods
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Dr. William D Berry, Mitchell Sanders
Although nearly all major social science departments offer graduate students training in quantitative methods, the typical sequencing of topics generally delays training in regression analysis and other multivariate techniques until a students second year. William Berry and Mitchell Sanderss Understanding Multivariate Research fills this gap with ...
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A Primer Multivar.Statistics 3rd
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Richard J Harris
This work covers various aspects of multivariate analysis of variance.
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Methods of Multivariate Analysis
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by
Alvin C Rencher
Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Methods of Multivariate Analysis was among those chosen. When measuring several variables on a complex experimental unit, it is often necessary to analyze the variables simultaneously, rather than isolate them and consider them individually. ...
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Multivariate Data Analysis
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by
Ronald L Tatham, Rolph E Anderson, William Black
For graduate-level courses in Marketing Research, Research Design and Data Analysis . Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis greatly reduces the amount of statistical notation and terminology used while focusing instead on the fundamental concepts that affect the use of specific ...
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Functional Data Analysis
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J Ramsay, B W Silverman
Scientists and others today often collect samples of curves and other functional observations. This monograph presents many ideas and techniques for such data. Included are expressions in the functional domain of such classics as linear regression, principal components analysis, linear modeling, and canonical correlation analysis, as well as ...
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Multivariate Analysis: Techniques for Educational and Psychological Research
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Maurice M Tatsuoka
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Theory and Application of the Linear Model
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by
Franklin A. Graybill
In THEORY AND APPLICATION OF THE LINEAR MODEL, Franklin A. Graybill integrates the linear statistical model within the context of analysis of variance, correlation and regression, and design of experiments. With topics motivated by real situations, it is a time tested, authoritative resource for experimenters, statistical consultants, and students.
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