[pt. A.] Statistical description of the quality of processes and measurements -- The normal distribution -- An introduction to hypothesis testing -- Some important hypothesis tests -- Analysis of variance -- Control charts -- Straight line regression and calibration -- Vectors and matrices -- Multiple and polynomial regression -- Non-linear regression -- Robust statistics -- Internal method validation -- Method validation by interlaboratory studies -- Other distributions -- The 2x2 contingency table -- Principal components -- Fuzzy methods -- Process modelling and sampling -- An introduction to experimental design -- Two-level factorial designs -- Fractional factorial designs -- Multi-level designs -- Mixture designs -- Other optimization methods -- Genetic algorithms and other global search strategies -- [pt. B.] Vectors, matrices and operations on matrices -- Cluster analysis -- Analysis of measurement tables -- Analysis of contingency tables -- Supervised pattern recognition -- Curve and mixture resolution by factor analysis and related techniques -- Relations between measurement tables -- Multivariate calibration -- Quantitative structure-activity relationships (QSAR) -- Analysis of sensory data -- Pharmacokinetic models -- Signal processing -- Kalman filtering -- Applications of operations research -- Artificial intelligence : expert and knowledge based systems -- Artificial neural networks.