Table of contents
About this book
Most of the observable phenomena in the empirical sciences are of multivariate nature. This book presents the tools and concepts of multivariate data analysis with a strong focus on applications. The text is devided into three parts. The first part is devoted to graphical techniques describing the distributions of the involved variables. The second part deals with multivariate random variables and presents from a theoretical point of view distributions, estimators and tests for various practical situations. The last part covers multivariate techniques and introduces the reader into the wide basket of tools for multivariate data analysis. The text presents a wide range of examples and 228 exercises.
ANOVA CAPM Cluster Analysis Conjoint Measurement Analysis Estimator Factor analysis Hypothesis Testing Multivariate Analysis Observable Projection Pursuit Random variable Sliced Inverse Regression correlation data analysis multidimensional scaling