Search results: 72
Material to be covered:
Reminder of measure theory
modes of convergence
law of large numbers
central limit theorem (via characteristic functions, Lindeberg principle, Stein's method)
stable laws
large deviations
martingales
References:
S.R.S. Varadhan, Probability Theory (Courant lecture notes), online notes
L. Breiman, Probability theory
F. den Hollander, Large Deviations
N. Zygouras, Discrete stochastic analysis
Notes on Large Deviations
This module is intended as a 12CATS introduction to mathematical
statistics to enable non-Statistics second-year students to study
sufficient material to make it possible to deal and benefit from the
final years modules in statistics offered by the Statistics Department.
ST221 covers concepts and methods of statistical modelling and model exploration. After this module you should be able to
- explain the theoretical background of linear statistical models and their extensions;
- fit a model to a given data set using R and interpret the resulting output;
- define, explore, evaluate and improve a fitted model.
Now that we are half-way through the module, I'd like to see how things are going so far with respect to the first three chapters, i.e. statistical models, transformations and approximation theorems. Based on the results of the feedback, I will provide you with additional videos/materials/resources on the topics that are causing more troubles, ensuring that you are on top of everything.Â