Requirements/prerequisites:

Duration: Michealmas, Hilary and Trinity

Number of lectures per week:

Assessment:

End-of-year Examination:

Description:

Basic Concepts of Inference.

Estimators, Mean squared Error, Sufficiency, MVUEs. Maximum likelihood estimation. Properties of maximum likelihood. Bayesian estimation.

Hypothesis testing, likelihood ratio tests. Bayesian methods. Other approaches: nonparametrics, order statistics, monte carlo methods - robustness.

The linear model. Least Squares estimates. BLUEs.

Extending the scope of the linear model: transformations, Box-Cox, Weighted regression. General and generalised linear models.

A Bayesian approach to inference.

Textbooks:

Silvey, S.D., ``Statistical Inference".

McCullagh and Nelder, ``Generalised Linear Models".

Lee, P., ``Bayesian Statistics: An Introduction".

Jun 10, 1998