This is an introductory course about Bayesian inference and modelling for data analysis. We will balance between theoretical and analytical tools and practice. In particular, for practical implementation of Bayesian models on real data we will make

Random walks 
Definition, Markovianity, temporal and spatial invariance, random walks with reflecting and absorbing barriers, reflection principle, ballot theorem, distribution of the maximum, hitting time theorem, first and second arc sine law,

This is an introductory course about Bayesian inference and modelling for data analysis. We will balance between theoretical and analytical tools and practice. In particular, for practical implementation of Bayesian models on real data we w

Learning goals. General learning targets:  The course is organised as a series of classes where the students will have the possibility to solve and discuss the solutions of a series of advanced exercises on the theory of stochastic processes. Â

The course provides a broad introduction to stochastic processes. In particular the aim is  - to give a rigorous introduction to the theory of stochastic processes, - to discuss the most important stochastic processes in some dept

The course provides a broad introduction to stochastic processes.  In particular the aim is   - to give a rigorous introduction to the theory of stochastic processes,  - to discuss the most important stochastic processes in some depth with exa

The course is organised as a series of classes where the students will have the possibility to solve and discuss the solutions of a series of simple and more advanced exercises on the theory of stochastic processes.  The students will a

This is a resource for setting up useful materials and communications to support students who need personal advice or help on topics related to Statistical Methods and Applications courses. You can find the contact details of the student tutors and t

The course provides a broad introduction to stochastic processes.  In particular the aim is   - to give a rigorous introduction to the theory of stochastic processes,  - to discuss the most important stochastic processes in some depth with exa

This course is intended for students with advanced knowledge of statistics. Being familiar with stochastic processes, computational techniques, and time series facilitates attendance in this class. 

The course provides a broad introduction to stochastic processes. In particular the aim is  - to give a rigorous introduction to the theory of stochastic processes, - to discuss the most important stochastic processes in some dept