• The course project is an individual assignment. If you use part of someone else’s work, you must include a citation for it.
• Pick a dataset and perform some sort of Bayesian analysis on it. Ideas for data: data you collected or from your lab, from a published paper or from the Internet, preferably in the broad area of Science and Engineering. The analysis performed must be Bayesian in some way.
• Make sure to credit the source of data or include a citation of it in your report. If the data are coming from a published paper, references should be provided or a pointer to the web source should be given. If the data file is small (≤ 10mb) and not sensitive, feel free to include it.
Project Deliverables
Including the data with your submission is optional. There are two required deliverables which will be uploaded to Canvas:
1. A pdf write-up of your project. This should include an introduction, analysis, results and conclusion. You are free to create this in LATEX, MS Word or whichever other editor you like. You are required to export it to pdf. There is no page requirement, but 4-7 page projects are fairly common.
Example Projects
• There is a sample project available on the course website. Please read it carefully and observe the format of the paper. This is the primary example of what we are expecting.
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ISyE 6420
Rats:Normalhierarchicalmodel
Pump:conjugategamma-Poissonhierarchicalmodel
Dogs:loglinearbinarymodel
Seeds:randomeffectslogisticregression
Surgical:institutionalranking
Magnesiummeta-analysispriorsensitivity
Salm:extra-Poissonvariationindose-responsestudy
• You are of course not limited to these. Any type of Bayesian analysis can serve as inspiration for this project. Please choose data and a topic that are interesting to you.
Grading and Evaluation
The Project is evaluated from 0 to 100 points. Creativity and originality are factors in high scores on the project. Typically the following rough guidelines are used:
• 90 points or lower: Very basic short project and/or there are errors in approach, techniques or conclusions.
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