Multivariate Data Analysis

"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

This 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

Examining your data. Multiple regression analysis. Multiple discriminat analysis. Multivariate analysis of variance. Canonical correlation analysis. Factor analysis. Cluster analysis. Multidimensional scaling. Conjoint analysis. Structural equation modeling.

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.

This is the first textbook that allows readers who may be unfamiliar with matrices to understand a variety of multivariate analysis procedures in matrix forms. By explaining which models underlie particular procedures and what objective function is optimized to fit the model to the data, it enables readers to rapidly

Making Sense of Multivariate Data Analysis is a short introduction to multivariate data analysis (MDA) for students and practitioners in the behavioral and social sciences. It provides a conceptual overview of the foundations of MDA and of a range of specific techniques including multiple regression, logistic regression, discriminant analysis, multivariate

Books about Multivariate Data Analysis

With a wealth of examples and exercises, this is a brand new edition of a classic work on multivariate data analysis. A key advantage of the work is its accessibility. This is because, in its focus on applications, the book presents the tools and concepts of multivariate data analysis in

Multivariate analysis plays an important role in the understanding of complex data sets requiring simultaneous examination of all variables. Breaking through the apparent disorder of the information, it provides the means for both describing and exploring data, aiming to extract the underlying patterns and structure. This intermediate-level textbook introduces the

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