Part 1 Descriptive statistics - compressing data: why one needs to analyze data? data representation and compression; analytic representation of random experimental data. Part 2 Modelling uncertainty: algorithmic complexity and random strings; statistical independence and Kolmogorov's probability theory; chaos in dynamical systems - how uncertainty arises in scientific and engineering phenomena. Part 3 Model specification - design of experiments: general principles of statistical analysis; statistical inference for normal populations; analysis of variance - uncertainty principle in signal processing and quantum mechanics, fuzzy systems and logic, a critique of pure reason, the remarkable Bernoulli family, uncertain virtual worlds mathematics packages.
