Fundamentals of Statistics contains material of various lectures and courses of H. Lohninger on statistics, data analysis and chemometrics......click here for more.

	Index
See also: univariate data, bivariate data
Multivariate Data   Basic knowledge Orthogonality The structure of the data Scatter matrix, covariance and cross correlation Selection of variables Optimization Introduction Phase space Response function Survey of methods Brute force approach Gradient descent methods Monte Carlo simulations Combination approaches Modeling PCA Factor Analysis MLR ANOVA Collinearity Selection of variables Stepwise regression Neural Networks Introduction ANNs as an abstract mapping machine Models of neural networks Generalisation and overtraining Extrapolation Selection of variables Training of neural networks Classification and Discrimination Introduction Linear discriminant analysis KNN classifier Cluster analysis Self organizing maps

Last Update: 2010-03-18