Module ST2352: Probability and Theoretical Statistics II
 Credit weighting (ECTS)
 5 credits
 Semester/term taught
 Hilary term 201213
 Contact Hours
 11 weeks, 3 lectures including tutorials per week
 Lecturer
 Prof. John Haslett (Statistics)
 Learning Outcomes
 On successful completion of this module, students should be able to:
 Model a 'stochastic system' by spreadsheet or similar using Monte Carlo methods;
 Model some stochastic systems through probability arguments;
 Use such models for problem solving;
 Model systems that arise in statistical analysis of data;
 Master the use of probability distribution theory in such modelling;
 Progress to Sophister modules in Statistics
 Module Content

 Reinforcement of probability theory by:
 The Monte Carlo approach to systems of random variables;
 Properties of Monte Carlo algorithms
 Transformations of elementary Uniform random variables;
 Conditional and rejection algorithms;
 The use of composite random variables;
 Frequently used univariate probability distributions;
 The study of joint, marginal and conditional distributions
 Probability theory will be developed for:
 Bivariate and multivariate probability distributions, including 'change of variable'
 The Multivariate Normal
 The theory of statistical inference will be introduced, and applied to:
 Sampling distributions for linear combinations including means, proportions, differences and simple linear regression;'
 An introduction to likelihood theory.
Module Prerequisite
ST2351
Assessment Detail
 This module will be examined jointly with ST2351 in a 3hour examination in Trinity term, except that those taking just one of the two modules will have a 2 hour examination. Continuous assessment will contribute 20% to the final grade for the module at the annual examination session. Supplemental examinations will consist of 100% exam.