Multivariate Data Analysis
Author: Joseph F. Hair (Jr.)
Publisher:
Published: 1995
Total Pages: 0
ISBN-13: 9780139133107
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Multivariate Data Analysis
Author: Joseph Hair
Publisher: Pearson Higher Ed
Published: 2016-08-18
Total Pages: 816
ISBN-13: 0133792684
DOWNLOAD EBOOKThis is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For graduate and upper-level undergraduate marketing research courses. For over 30 years, Multivariate Data Analysis has provided readers 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 research into fundamental concepts, the text explains to readers how to understand and make use of the results of specific statistical techniques. In this Seventh Edition, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques.
Making Sense of Multivariate Data Analysis
Author: John Spicer
Publisher: SAGE
Published: 2005
Total Pages: 256
ISBN-13: 9781412904018
DOWNLOAD EBOOKA 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.
An Introduction to Applied Multivariate Analysis with R
Author: Brian Everitt
Publisher: Springer Science & Business Media
Published: 2011-04-23
Total Pages: 284
ISBN-13: 1441996508
DOWNLOAD EBOOKThe 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.
Multivariate Statistical Analysis
Author: Parimal Mukhopadhyay
Publisher: World Scientific Publishing Company
Published: 2008-11-25
Total Pages: 568
ISBN-13: 9813107111
DOWNLOAD EBOOKThis 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.
Reading and Understanding Multivariate Statistics
Author: Laurence G. Grimm
Publisher:
Published: 1995
Total Pages: 373
ISBN-13:
DOWNLOAD EBOOKExploratory Multivariate Analysis by Example Using R
Author: Francois Husson
Publisher: CRC Press
Published: 2017-04-25
Total Pages: 263
ISBN-13: 1315301865
DOWNLOAD EBOOKFull of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) a
Applied Multivariate Statistical Analysis
Author: Wolfgang Karl Härdle
Publisher: Springer Nature
Published:
Total Pages: 611
ISBN-13: 3031638336
DOWNLOAD EBOOKModern Multivariate Statistical Techniques
Author: Alan J. Izenman
Publisher: Springer Science & Business Media
Published: 2009-03-02
Total Pages: 757
ISBN-13: 0387781897
DOWNLOAD EBOOKThis 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.
Practical Multivariate Analysis
Author: Abdelmonem Afifi
Publisher: CRC Press
Published: 2019-10-16
Total Pages: 534
ISBN-13: 1351788906
DOWNLOAD EBOOKThis 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.
