Modern Multivariate Statistical Techniques PDF Download
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Author | : Alan J. Izenman |
Publisher | : Springer Science & Business Media |
Total Pages | : 757 |
Release | : 2009-03-02 |
Genre | : Mathematics |
ISBN | : 0387781897 |
Download Modern Multivariate Statistical Techniques Book in PDF, ePub and Kindle
This 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.
Author | : Alan J. Izenman |
Publisher | : Springer |
Total Pages | : 733 |
Release | : 2013-03-11 |
Genre | : Mathematics |
ISBN | : 9780387781884 |
Download Modern Multivariate Statistical Techniques Book in PDF, ePub and Kindle
This 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.
Author | : Norou Diawara |
Publisher | : Springer |
Total Pages | : 177 |
Release | : 2019-06-29 |
Genre | : Mathematics |
ISBN | : 3030114317 |
Download Modern Statistical Methods for Spatial and Multivariate Data Book in PDF, ePub and Kindle
This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques. Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.
Author | : Thomas Cleff |
Publisher | : Springer |
Total Pages | : 488 |
Release | : 2019-07-10 |
Genre | : Business & Economics |
ISBN | : 303017767X |
Download Applied Statistics and Multivariate Data Analysis for Business and Economics Book in PDF, ePub and Kindle
This textbook will familiarize students in economics and business, as well as practitioners, with the basic principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it demonstrates the methods of univariate, bivariate, and multivariate statistical analysis. The textbook covers a range of topics, from data collection and scaling to the presentation and simple univariate analysis of quantitative data, while also providing advanced analytical procedures for assessing multivariate relationships. Accordingly, it addresses all topics typically covered in university courses on statistics and advanced applied data analysis. In addition, it does not limit itself to presenting applied methods, but also discusses the related use of Excel, SPSS, and Stata.
Author | : Kim H. Esbensen |
Publisher | : Multivariate Data Analysis |
Total Pages | : 622 |
Release | : 2002 |
Genre | : Experimental design |
ISBN | : 9788299333030 |
Download Multivariate Data Analysis Book in PDF, ePub and Kindle
"Multivariate Data Analysis - in practice adopts a practical, non-mathematical approach to multivariate data analysis. The book's principal objective is to provide a conceptual framework for multivariate data analysis techniques, enabling the reader to apply these in his or her own field. Features: Focuses on the practical application of multivariate techniques such as PCA, PCR and PLS and experimental design. Non-mathematical approach - ideal for analysts with little or no background in statistics. Step by step introduction of new concepts and techniques promotes ease of learning. Theory supported by hands-on exercises based on real-world data. A full training copy of The Unscrambler (for Windows 95, Windows NT 3.51 or later versions) including data sets for the exercises is available. Tutorial exercises based on data from real-world applications are used throughout the book to illustrate the use of the techniques introduced, providing the reader with a working knowledge of modern multivariate data analysis and experimental design. All exercises use The Unscrambler, a de facto industry standard for multivariate data analysis software packages. Multivariate Data Analysis in Practice is an excellent self-study text for scientists, chemists and engineers from all disciplines (non-statisticians) wishing to exploit the power of practical multivariate methods. It is very suitable for teaching purposes at the introductory level, and it can always be supplemented with higher level theoretical literature."Résumé de l'éditeur.
Author | : Rand R. Wilcox |
Publisher | : Gulf Professional Publishing |
Total Pages | : 688 |
Release | : 2003-01-06 |
Genre | : Mathematics |
ISBN | : 9780127515410 |
Download Applying Contemporary Statistical Techniques Book in PDF, ePub and Kindle
Applying Contemporary Statistical Techniques explains why traditional statistical methods are often inadequate or outdated when applied to modern problems. Wilcox demonstrates how new and more powerful techniques address these problems far more effectively, making these modern robust methods understandable, practical, and easily accessible. Highlights: * Assumes no previous training in statistics * Explains when and why modern methods provide more accurate results * Provides simple descriptions of when and why conventional methods can be highly unsatisfactory * Covers the latest developments on multiple comparisons * Includes recent advances in risk-based methods * Features many illustrations and examples using data from real studies * Describes and illustrates easy-to-use s-plus functions for applying cutting-edge techniques "The book is quite unique in that it offers a lot of up-to-date statistical tools. No other book at this level comes close in this aspect." Xuming He -University of Illinois, Urbana
Author | : Wolfgang Härdle |
Publisher | : Springer Science & Business Media |
Total Pages | : 367 |
Release | : 2007-07-27 |
Genre | : Computers |
ISBN | : 0387707840 |
Download Multivariate Statistics: Book in PDF, ePub and Kindle
The authors have cleverly used exercises and their solutions to explore the concepts of multivariate data analysis. Broken down into three sections, this book has been structured to allow students in economics and finance to work their way through a well formulated exploration of this core topic. The first part of this book is devoted to graphical techniques. The second deals with multivariate random variables and presents the derivation of estimators and tests for various practical situations. The final section contains a wide variety of exercises in applied multivariate data analysis.
Author | : Abdelmonem Afifi |
Publisher | : CRC Press |
Total Pages | : 528 |
Release | : 2019-10-16 |
Genre | : Mathematics |
ISBN | : 1351788906 |
Download Practical Multivariate Analysis Book in PDF, ePub and Kindle
This 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.
Author | : Kaitai Fang |
Publisher | : World Scientific |
Total Pages | : 470 |
Release | : 2005 |
Genre | : Mathematics |
ISBN | : 9812567763 |
Download Contemporary Multivariate Analysis and Design of Experiments Book in PDF, ePub and Kindle
Index. Subject index -- Author index
Author | : Thomas D. Wickens |
Publisher | : Psychology Press |
Total Pages | : 216 |
Release | : 2014-02-25 |
Genre | : Psychology |
ISBN | : 1317780221 |
Download The Geometry of Multivariate Statistics Book in PDF, ePub and Kindle
A traditional approach to developing multivariate statistical theory is algebraic. Sets of observations are represented by matrices, linear combinations are formed from these matrices by multiplying them by coefficient matrices, and useful statistics are found by imposing various criteria of optimization on these combinations. Matrix algebra is the vehicle for these calculations. A second approach is computational. Since many users find that they do not need to know the mathematical basis of the techniques as long as they have a way to transform data into results, the computation can be done by a package of computer programs that somebody else has written. An approach from this perspective emphasizes how the computer packages are used, and is usually coupled with rules that allow one to extract the most important numbers from the output and interpret them. Useful as both approaches are--particularly when combined--they can overlook an important aspect of multivariate analysis. To apply it correctly, one needs a way to conceptualize the multivariate relationships that exist among variables. This book is designed to help the reader develop a way of thinking about multivariate statistics, as well as to understand in a broader and more intuitive sense what the procedures do and how their results are interpreted. Presenting important procedures of multivariate statistical theory geometrically, the author hopes that this emphasis on the geometry will give the reader a coherent picture into which all the multivariate techniques fit.