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◄Faculty of Business and Economics►

AA037017 BAYESIAN STATISTICS
4 Credits

Learning Outcomes At the end of the course, students are able to:
(1) Develop models based on the foundations of Bayesian
statistics;
(2) Determine different approaches to the choice of prior
distribution;
(3) Adapt to the computational implementation of Bayesian
analysis;
(4) Use the Bayesian approach in solving real world
problems.

Synopsis of Course This course expose students to Bayesian approach to
Contents statistical inference. Topics covered includes the foundation of
Bayesian statistics, determining prior distribution, Bayesian
inference, Bayesian decision theory and computational tools
for inferences. Students will learn statistical software for
Bayesian analysis and apply the Bayesian approach to real
world problems.

Assessment Weightage Continuous Assessment : 60%
Final Examination: 40%

Medium of Instruction English

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