TUBAFdigital - Stochastic Methods for Materials Science

The objective of this course is to convey an understanding of the role of stochastic modelling and stochastic algorithms for materials science. The range of topics includes

• basics in probability theory (random variables, distributions, characteristics, limit theorems)
• basics in statistics (graphics, estimation and confidence, hypothesis testing)
• regression analysis (linear models, least squares, statistics, nonlinear regression),
• stochastic models for random materials (Poisson process, Boolean model, random packings, random mosaics)
• stochatic simulation (Monte Carlo and Markov chain Monte Carlo algorithm)