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Module ST2352: Probability and Theoretical Statistics II

Credit weighting (ECTS)
5 credits
Semester/term taught
Hilary term 2012-13
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 spread-sheet 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 3-hour 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.