Bayesian Inference - Fall 2011 - Final project
The final exam will be a team project on a topic selected by the team. The topic can either be a
Bayesian analysis of an important and challenging data set or methodological work on
topic of interest to Bayesians, perhaps a simulation study comparing several methods.
The projects are to be done in groups of 1-2 chosen by the instructor with student input.
They are to result in thorough but concise, professional quality technical poster presentation.
Project abstract due: October 26
One-page proposals are due in class by the deadline stated above. These
proposals should list your team members and spell out briefly the main goal
of the study, your basic approach, and the role of each team member. Also include
the day(s) your group prefers to present the project.
Pick a subject that interests you (preferable on a topic of your future/current dissertation)! IMPORTANT: The problem
you choose should not be something that you have already done! For example,
if you have already taken the written prelim exam, you should not use the same
topic here; you should identify a completely new problem. Similarly, if you are
carrying out simulations as part of your dissertation research already, you should
not use this as the basis for your project. Some part of your
instructor's reaction to your project will also inevitably reflect the
originality of your topic, so choose it with some care. This project need not be computationally expensive nor require a huge time investment in data collection.
But it does need to show careful planning, good logic and the Bayesian analysis
concepts discussed in the course. If you are having trouble
identifying a topic, please see the instructor as soon as possible.
Final report due December 7
The final product of the project will be a poster, which you should turn in to the instructor and present in class. The poster should include:
- Motivation for studying this problem
- A description of data and/or methods to be used
- Discussion of the major findings
- A statement of the implications of your study
- A discussion of further questions raised by your study
Grading
Team average scores for these projects will be assigned following:
- Quality and novelty of the analysis and/or methodology, 60%
- Professional appearance and clarity of the poster, 20%
- Poster presentation, 20%
Groups
Peng & Ze
Amanda & Sarah
Ander & Daniel
Yigfang & Runchao
Bo & Liwei
Sam & Samantha
Colin & Qian
Wei & Kristen
Alredo
William
Ryan
Ben
Sayantan
Yiwei