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

Index

Editorial Introduction Basic Concepts General Processing Steps Univariate Data Statistical Tests Bivariate Data Multivariate Data Introduction Survey on Multivariate Methods Basic Knowledge Experimental Design Optimization Modeling Introduction Multivariate Calibration Modeling - An Example Modeling with latent variables Validation of Models Multiple Regression PCA Factor Analysis PLS Neural Networks Natural Brains Introduction Mapping of Spaces Neural Networks - Model Selection Taxonomy of ANNs Models of Neural Networks Recurrent Networks Multilayer Perceptron Kohonen Networks RBF Neural Networks RBF Neural Networks RBF Network as Kernel Estimator Generalization and Overtraining Extrapolation Growing Neural Networks Common Questions about ANNs Classification and Discrimination Math Background Exercises Appendix