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Statistical Inference

Date: 25th - 28th October 2011
Duration: 2 days
Delivered by: Dr Emma Eastoe

Registration deadline has passed.
Please contact psc@lancaster.ac.uk for more information about this course.

Cost
The course fees include all supporting documentation and refreshments.
  • External from industry/commerce - £510
  • External postgraduate student - £300
  • Lancaster University staff - £120
  • External from academic institution/public sector/charity - £440
  • Lancaster University postgraduate student - £60
  • Members of Mathematics and Statistics at Lancaster University - £ 0
Course description

The main aim of this module is to give a solid foundation to the understanding of statistics as a general approach to the problem of making valid inferences about relationships using data from observational or experimental studies. Examples of analyses from the social sciences will be used to illustrate this approach. The emphasis will be on the principle of Likelihood as a unifying theory for the development of statistical analysis.

Some prior knowledge of probability theory and statistical methods is required.

Topics covered
  • Revision of probability theory and parametric statistical models
  • The properties of statistical hypothesis tests, statistical estimation and sampling distributions
  • Maximum Likelihood Estimation of model parameters
  • Asymptotic distributions of the maximum likelihood estimator and associated statistics for use in hypothesis testing
  • Application of likelihood inference to simple statistical analyses including linear regression and contingency tables
Learning
Students will learn through the application of concepts and techniques covered in the module by application to real data sets. Students will be encouraged to examine issues of substantive interest in these studies.
Students will acquire knowledge of:
  • the basic principles of probability theory
  • the properties of a statistical test
  • Maximum Likelihood as a theory for estimation and inference
  • the application of the methodology to hypothesis testing for model parameters, the analysis of contingency tables and linear regression
  • apply theoretical concepts
  • identify and solve problems
Cancellation Policy
Registrations are transferable to another course or individual at any time. Full refunds will be given for cancellation 10 or more working days before the course start date. Otherwise the full course fee will be charged.