Multivariate+Methods

Multivariate Methods (GWU EMSE-271 Data Analysis for Engineers and Scientists)
Index | Topics (Logical Lectures) | Lectures | Problems | Readings | Nomenclature | Concepts

[ Introduction | Regression: Analysis | Principal Components: Analysis | Factor Analysis | Multidimensional Scaling | Clustering | Canonical Correlation | Structured Equation Models with Latent Variables | Analysis of Variance: Variations, Analysis | Discriminant Analysis | Logit Choice Models ] [Not Covered in Lattin:. . . ]

"**Multivariate analysis (MVA)** is based on the statistical principle of multivariate statistics, which involves observation and analysis of more than one statistical variable at a time. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest." - [|Wikipedia]

The Preface of Analyzing Multivariate Datapoints out the book is intended for the data analyzer.

The categoriztion of methods is Chapter 1 is good. And the Preface points out that Automatic Interaction Detection (AID) and Monotonic Analysis of Variance (MONANONA) have been removed from this edition. analysis is still not covered.

The provides a couple of pages on Obersvations and Data and Levels of Measurement that describe the data the methods analyze then an overview of the methods in the book (See Multivariate Methods Introduction page).


 * Sources**


 * Analyzing Multivariate Data, by James Lattin, Douglas Carroll and Green ([|Amazon]), Preface, pages xxi-xxii
 * Multivariate analysis. (2009, November 30). In //Wikipedia, The Free Encyclopedia//. Retrieved 16:09, December 1, 2009, from []