Fundamentals of Statistics
contains material of various lectures and courses of H. Lohninger on statistics, data analysis and chemometrics...
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Index
Editorial
Changes and Improvements
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
MLR
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
Single Processing Unit
Multi-layer Perceptron
Back Propagation of Errors
Kohonen Networks
RBF Neural Networks
Generalization and Overtraining
Extrapolation
Growing Neural Networks
Common Questions about ANNs
Classification and Discrimination
Math Background
Exercises
Appendix
Last Update: 2012-10-08