Student guide Faculty of Engineering A.Y. 2007/08

The course provides an introduction to the principles of the statistical processing of experimental data, starting from the fundamental results of probability theory. Particular emphasis is given to the analysis of the conceptual and practical limitations arising from the presence of measurement uncertainty.

Mathematical Analysis I -

1. Introduction to the analysis of experimental data: accuracy and significance; dimensional analysis.
2. Elements of descriptive statistics.
3. Introduction to probability calculations according to the Kolmogorov axiom theory.
- The measurement of probability and its frequentist interpretation.
- The theorems of probability.
- Random variables, random vectors and their transformations: notable distributions.
- Asymptotic results.
4. Introduction to probabilistic models in engineering and physics.
5. Elements of parametric statistical inference.
6. Error and uncertainty: expression of measurement results.

The examination procedure will be communicated during the course.

Study materials distributed by the lecturers (slides, notes, …)
Further reading:
Papoulis A., Pillai S.U., Probability, random variables and stochastic processes, McGraw-Hill, 2002
Lira I., Evaluating the measurement uncertainty, IOP, 2002