Bayesian Statistics
Course category:
3rd year
Module code:
0530001
Year:
2010/11
Term:
Spring
Credits:
10
Lecturer:
Dr Peter Lee AimsThe aim of the module is to introduce the basic notions of Bayesian statistics, showing how Bayes Theorem provides a natural way of combining prior information with experimental data to arrive at a posterior probability distribution over parameters and to show the differences between classical (sampling theory) statistics and Bayesian statistics. Learning objectivesAt the end of the module you should be able:
Syllabus
Recommended texts
Teaching
AssessmentOne and a half hour closed examination towards the end of the Summer Term 90%, Elective informationA course on Bayesian statistics showing how to make inferences by combining prior beliefs with information obtained from experimental data. Please check prerequisites carefully before asking to take this module as an elective. Prerequisites


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