THEORY OF STATISTICS 16.5 AssocProf R K Watson Special requirement: An electronic calculator of an approved type (refer to Department of Statistics Office) Statistics 619-201. Second semester 39 lectures (three a week) and 39 tutorial/practice class hours Students completing this course should

Comprehend:

  • the fundamental concepts of probability theory;
  • the theory underlying statistical inference;
  • the basic principles of experimental design;
  • Have developed the skills:
  • to use probability models and distribution theory in applications to standard situations;
  • to carry out standard statistical analyses;

Appreciate:

  • the breadth of application of probability and statistics;
  • the importance of the underlying mathematical theory of statistics;
  • the application of computer software in probability calculations, simulation and statistical analysis.
Elementary probability concepts; probability models; sequences of independent trials; regenerative phenomena; introduction to Markov chains and simple Markov processes; simulation methods; conditional distributions and conditional expectations; generating functions and applications including the central limit theorem. Estimation of parameters of probability distributions; desirable properties of estimators: consistency, unbiasedness and efficiency; maximum likelihood estimation; confidence intervals and hypothesis testing; likelihood ratio tests; an introduction to distribution-free methods; the theory and applications of the general linear model - with particular reference to regression problems including multiple and polynomial regression, the analysis of one-way and two-way classifications and the analysis of standard statistical experiments; the basic principles of experimental design. Up to 3 hours end-of semester written examination; up to 50 pages of assignments may be assessed. THEORY OF STATISTICS 16.5 Assoc Prof R K Watson Special requirement: An electronic calculator of an approved type (refer to Department of Statistics Office) Statistics 619-201. Second semester 39 lectures (three a week) and 39 tutorial/practice class hours Students completing this course should

Comprehend:

  • the fundamental concepts of probability theory;
  • the theory underlying statistical inference;
  • the basic principles of experimental design;

Have developed the skills:

  • to use probability models and distribution theory in applications to standard situations;
  • to carry out standard statistical analyses;

Appreciate:

  • the breadth of application of probability and statistics;
  • the importance of the underlying mathematical theory of statistics;
  • the application of computer software in probability calculations, simulation and statistical analysis.
Elementary probability concepts; probability models; sequences of independent trials; regenerative phenomena; introduction to Markov chains and simple Markov processes; simulation methods; conditional distributions and conditional expectations; generating functions and applications including the central limit theorem. Estimation of parameters of probability distributions; desirable properties of estimators: consistency, unbiasedness and efficiency; maximum likelihood estimation; confidence intervals and hypothesis testing; likelihood ratio tests; an introduction to distribution-free methods; the theory and applications of the general linear model - with particular reference to regression problems including multiple and polynomial regression, the analysis of one-way and two-way classifications and the analysis of standard statistical experiments; the basic principles of experimental design. Up to 3 hours end-of semester written examination; up to 50 pages of assignments may be assessed.