Multivariate Data Analysis - in Practice

An Introduction to Multivariate Data Analysis and Experimental Design

Author: Kim H. Esbensen,Dominique Guyot,Frank Westad,Lars P. Houmoller

Publisher: Multivariate Data Analysis

ISBN: 9788299333030

Category: Experimental design

Page: 598

View: 4943

DOWNLOAD NOW »

"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.
Release

Multivariate Data Analysis

Author: Joseph F. Hair (Jr),William C. Black,Barry J. Babin,Rolph E. Anderson

Publisher: N.A

ISBN: 9781292021904

Category: Multivariate analysis

Page: 752

View: 7697

DOWNLOAD NOW »

Offering an applications-oriented approach which focuses on the use of each technique rather than its mathematical derivation, this textbook introduces a six-step framework for organising and discussing multivariate data analysis techniques.
Release

Multivariate Data Analysis

A Global Perspective

Author: Joseph F. Hair

Publisher: Prentice Hall

ISBN: 9780135153093

Category: Multivariate analysis

Page: 800

View: 9260

DOWNLOAD NOW »

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 research into fundamental concepts, the text explains to students how to understand and make use of the results of specific statistical techniques. In this seventh revision, 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
Release

Multivariate data analysis with readings

Author: Joseph F. Hair

Publisher: Pearson College Div

ISBN: 9780023490200

Category: Mathematics

Page: 757

View: 488

DOWNLOAD NOW »

Ch. 1. Introduction -- Ch. 2. Examining Your Data -- Ch. 3. Multiple Regression Analysis -- Ch. 4. Multiple Discriminant Analysis -- Ch. 5. Multivariate Analysis of Variance -- Ch. 6. Canonical Correlation Analysis -- Ch. 7. Factor Analysis -- Ch. 8. Cluster Analysis -- Ch. 9. Multidimensional Scaling -- Ch. 10. Conjoint Analysis -- Ch. 11. Structural Equation Modeling -- Appendix A: Applications of Multivariate Data Analysis.
Release

Multivariate Data Analysis

Author: Joseph F. Hair

Publisher: N.A

ISBN: 9780138948580

Category: Multivariate analysis

Page: 730

View: 5430

DOWNLOAD NOW »

For graduate courses in Marketing Research, Research Design and Data Analysis. For the non-statistician, this applications-oriented introduction to multivariate analysis reduces the amount of statistical notation and terminology used while focusing on the fundamental concepts that affect the use of specific techniques.
Release

Multivariate Statistical Modeling and Data Analysis

Proceedings of the Advanced Symposium on Multivariate Modeling and Data Analysis May 15–16, 1986

Author: H. Bozdogan,Arjun K. Gupta

Publisher: Springer Science & Business Media

ISBN: 9400939779

Category: Mathematics

Page: 189

View: 8177

DOWNLOAD NOW »

This volume contains the Proceedings of the Advanced Symposium on Multivariate Modeling and Data Analysis held at the 64th Annual Heeting of the Virginia Academy of Sciences (VAS)--American Statistical Association's Vir ginia Chapter at James Madison University in Harrisonburg. Virginia during Hay 15-16. 1986. This symposium was sponsored by financial support from the Center for Advanced Studies at the University of Virginia to promote new and modern information-theoretic statist ical modeling procedures and to blend these new techniques within the classical theory. Multivariate statistical analysis has come a long way and currently it is in an evolutionary stage in the era of high-speed computation and computer technology. The Advanced Symposium was the first to address the new innovative approaches in multi variate analysis to develop modern analytical and yet practical procedures to meet the needs of researchers and the societal need of statistics. vii viii PREFACE Papers presented at the Symposium by e1l11lJinent researchers in the field were geared not Just for specialists in statistics, but an attempt has been made to achieve a well balanced and uniform coverage of different areas in multi variate modeling and data analysis. The areas covered included topics in the analysis of repeated measurements, cluster analysis, discriminant analysis, canonical cor relations, distribution theory and testing, bivariate densi ty estimation, factor analysis, principle component analysis, multidimensional scaling, multivariate linear models, nonparametric regression, etc.
Release

Making Sense of Multivariate Data Analysis

An Intuitive Approach

Author: John Spicer

Publisher: SAGE

ISBN: 9781412904018

Category: Mathematics

Page: 233

View: 8916

DOWNLOAD NOW »

′This book is a helpful guide to reading and understanding multivariate data analysis results in social and psychological research′ _C. Y. Joanne Peng, Indiana University at Bloomington ′This book serves as a resource for readers who want to have an overall view of what encompasses multivariate analyses. The author has discussed some important issues rather philosophically (e.g., theory vs. data analysis). These points are valuable even for readers who have extensive training with multivariate analyses′ _Jenn-Yun Tein, Arizona State University
Release

MULTIVARIATE DATA ANALYSIS

Using SPSS and AMOS

Author: R. Shanthi

Publisher: MJP Publisher

ISBN: N.A

Category: Mathematics

Page: 448

View: 2027

DOWNLOAD NOW »

Multivariate Data Analysis Introduction to SPSS Outliers Normality Test of Linearity Data Transformation Bootstrapping Homoscedasticity Introduction to IBM SPSS – AMOS Multivariate Analysis of Variance (MANOVA) One Way Manova in SPSS Multiple Regression Analysis Binary Logistic Regression Factor Analysis Exploratory Factor Analysis Confirmatory Factor Analysis Cluster Analysis K - Mean Cluster Analysis Hierarchical Cluster Analysis Discriminant Analysis Correspondence Analysis Multidimensional Scaling Example - Multidimensional Scaling (ALSCAL) Neural Network Decision Trees Path Analysis Structural Equation Modeling Canonical Correlation
Release

Applied Multivariate Statistical Analysis

Author: Wolfgang Karl Härdle,Léopold Simar

Publisher: Springer

ISBN: 3662451719

Category: Business & Economics

Page: 580

View: 1936

DOWNLOAD NOW »

Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners. All chapters include practical exercises that highlight applications in different multivariate data analysis fields. All of the examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate Statistical Analysis offers the following new features: A new chapter on Variable Selection (Lasso, SCAD and Elastic Net) All exercises are supplemented by R and MATLAB code that can be found on www.quantlet.de. The practical exercises include solutions that can be found in Härdle, W. and Hlavka, Z., Multivariate Statistics: Exercises and Solutions. Springer Verlag, Heidelberg.
Release