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Author: Heinz Kres Publisher: Springer Science & Business Media ISBN: 1461256097 Category : Mathematics Languages : en Pages : 523
Book Description
An English translation of my "Statistisahe Tafeln zur multivariaten Analysis - Ein Handbuah mit Hinweisen zur Anwendung" was planned already in 1975 when I prepared the German volume. The tables were immediately supplied with German and English headings for the inten ded photo-offset printing. In the meantime. new and important tables for multivariate statistiaal hypotheses and proaedures have been aompiled and published. Only four of them have been inaorporated in the present volume. The seleation of these tables must be on an individual basis for reasons of spaae. Let me mention only the new tables for sample size determination in MANOVA. The instruations for using the tables are all organized in the same way. They are kept short sinae it is not the task of suah a work to provide an introduation to the theory and praatiae of multivariate analysis. I have renounaed giving examples for the same reason. I wish instead to refer the reader to the many good textbooks that are avai lable. as well as to my own works on methods that are in preparation. Furthermore. I am of the opinion that statistiaal tables should aaaom pany the textbook rather than be inaluded in it. vii viii Finally, my thanks go to the translator, Mr. Peter R. Wadsack, as ~ell as to the ladies and gentlemen of Springer-Verlag for their pleasant collaboration and their indulgence of my numerous requests
Author: Heinz Kres Publisher: Springer Science & Business Media ISBN: 1461256097 Category : Mathematics Languages : en Pages : 523
Book Description
An English translation of my "Statistisahe Tafeln zur multivariaten Analysis - Ein Handbuah mit Hinweisen zur Anwendung" was planned already in 1975 when I prepared the German volume. The tables were immediately supplied with German and English headings for the inten ded photo-offset printing. In the meantime. new and important tables for multivariate statistiaal hypotheses and proaedures have been aompiled and published. Only four of them have been inaorporated in the present volume. The seleation of these tables must be on an individual basis for reasons of spaae. Let me mention only the new tables for sample size determination in MANOVA. The instruations for using the tables are all organized in the same way. They are kept short sinae it is not the task of suah a work to provide an introduation to the theory and praatiae of multivariate analysis. I have renounaed giving examples for the same reason. I wish instead to refer the reader to the many good textbooks that are avai lable. as well as to my own works on methods that are in preparation. Furthermore. I am of the opinion that statistiaal tables should aaaom pany the textbook rather than be inaluded in it. vii viii Finally, my thanks go to the translator, Mr. Peter R. Wadsack, as ~ell as to the ladies and gentlemen of Springer-Verlag for their pleasant collaboration and their indulgence of my numerous requests
Author: Keenan A. Pituch Publisher: Routledge ISBN: 1317805925 Category : Psychology Languages : en Pages : 814
Book Description
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.
Author: Mukhopadhyay Parimal Publisher: World Scientific Publishing Company ISBN: 9813107111 Category : Mathematics Languages : en Pages : 568
Book Description
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.
Author: S. James Press Publisher: ISBN: Category : Analysis of variance Languages : en Pages : 554
Book Description
Textbook on methodology and model-building techniques of multivariate statistical analysis, with particular reference to applications in the social sciences - includes a bibliography pp. 483 to 509, graphs and statistical tables.
Author: Richard A. Johnson Publisher: Pearson ISBN: 9780134995397 Category : Multivariate analysis Languages : en Pages : 808
Book Description
This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price. Please visit www.pearsonhighered.com/math-classics-series for a complete list of titles. 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 multivariate observations. Its primary goal is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Ideal for a junior/senior or graduate level course that explores the statistical methods for describing and analyzing multivariate data, the text assumes two or more statistics courses as a prerequisite.
Author: Brian Everitt Publisher: Springer Science & Business Media ISBN: 1441996508 Category : Mathematics Languages : en Pages : 284
Book Description
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.
Author: Daniel Zelterman Publisher: Springer Nature ISBN: 3031130057 Category : Medical Languages : en Pages : 469
Book Description
Now in its second edition, this book brings multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source shareware program R, Dr. Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays; linear algebra; univariate, bivariate and multivariate normal distributions; factor methods; linear regression; discrimination and classification; clustering; time series models; and additional methods. He uses practical examples from diverse disciplines, to welcome readers from a variety of academic specialties. Each chapter includes exercises, real data sets, and R implementations. The book avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary. New to this edition are chapters devoted to longitudinal studies and the clustering of large data. It is an excellent resource for students of multivariate statistics, as well as practitioners in the health and life sciences who are looking to integrate statistics into their work.
Author: Alvin C. Rencher Publisher: John Wiley & Sons ISBN: 0471461725 Category : Mathematics Languages : en Pages : 739
Book Description
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. Multivariate analysis enables researchers to explore the joint performance of such variables and to determine the effect of each variable in the presence of the others. The Second Edition of Alvin Rencher's Methods of Multivariate Analysis provides students of all statistical backgrounds with both the fundamental and more sophisticated skills necessary to master the discipline. To illustrate multivariate applications, the author provides examples and exercises based on fifty-nine real data sets from a wide variety of scientific fields. Rencher takes a "methods" approach to his subject, with an emphasis on how students and practitioners can employ multivariate analysis in real-life situations. The Second Edition contains revised and updated chapters from the critically acclaimed First Edition as well as brand-new chapters on: Cluster analysis Multidimensional scaling Correspondence analysis Biplots Each chapter contains exercises, with corresponding answers and hints in the appendix, providing students the opportunity to test and extend their understanding of the subject. Methods of Multivariate Analysis provides an authoritative reference for statistics students as well as for practicing scientists and clinicians.
Author: Heinz Kres
Author: Heinz Kres
Author: Heinz Kres
Author: Keenan A. Pituch
Author: Mukhopadhyay Parimal
Author: S. James Press
Author: K. C. Sreedharan Pillai
Author: Richard A. Johnson
Author: Brian Everitt
Author: Daniel Zelterman
Author: Alvin C. Rencher