Multivariate analysis : an application-oriented introduction

Table of Contents: 1.Introduction to empirical data analysis 2.Regression analysis 3.Analysis of variance 4.Discriminant analysis 5.Logistic regression 6.Contingency analysis 7.Factor analysis 8.Cluster analysis 9.Conjoint analysis

If we are able to extract useful information from data, it can be incredibly valuable. For this reason, multivariate data analysis is vital in business and science. This book provides an accessible introduction to the most relevant multivariate data analysis techniques. It is entirely application-oriented, requires minimal understanding of mathematics and statistics, teaches the procedures with numerical examples, and illustrates each method with a case study done using IBM's SPSS statistical software. Extensions of the approaches and connections to other procedures are described, as well as application recommendations. An introduction chapter introduces the fundamental concepts of the multivariate methods discussed in the text and reviews statistical fundamentals applicable to all approaches.