Perform a professional analysis using everything you've learned in ISYE 6414 and write it up in a professional, academic manner resembling what one would see in a peer-reviewed paper.
Your group must find and use at least 3 datasets from 3 different data sources, combine them in an interesting way, and test questions or assumptions about the information they contain. See the data sources requirement for details.
Team Project Requirements
This is a team project — you cannot work solo. You can (and should!) form a team of 5, but if you don't, we'll eventually assign you to one.
Choose Your Own Topic
Your team must choose your own research topic and problem to investigate. There are no pre-defined project skeletons this semester — you have full freedom (and responsibility) to identify a problem that interests your team and can be addressed with the statistical methods from this course.
How the Project Runs
The project is one completion-only milestone followed by three deliverables graded against published rubrics. Each builds on the one before it — this is a single project carried through the semester, not four separate assignments.
The complete analysis, written up as a professional paper.
Dec 13, 2026, 11:59 PM US Eastern Time
Four weeks to form teams
You have until Sep 20, 2026, 11:59 PM US Eastern Time to form a team and settle on a topic — deliberately generous, so teams stop reshuffling and start working. Anyone still unassigned after that is assigned to a team by the instructor.
Some people will likely drop the course. If groups become much too small, we'll reassign/combine groups to maintain appropriate team sizes.
Smaller Teams, Same Standards
Teams that choose to remain smaller than 4-5 members will be graded at the same level as full-sized teams. The Final Report requirements (page length, number of analyses, citations, etc.) remain the same regardless of team size.
Everyone is expected to contribute to each element of the project. If you don't contribute adequately, you'll be penalized (up to being given a 0 for that deliverable).
Project Timeline
gantt
title ISYE 6414 Final Project Timeline (Summer 2026)
dateFormat YYYY-MM-DD
axisFormat %b %-d
section Team
Team Formation :t1, 2026-05-18, 13d
Teams Due :milestone, tm, 2026-05-31, 0d
section Analysis Plan
Analysis Plan Work :ap1, after tm, 30d
Analysis Plan Due :milestone, apm, 2026-06-30, 0d
Feedback & Grades Returned :milestone, apfb, 2026-07-08, 0d
section Peer Reviews
Peer Reviews :pr1, 2026-07-24, 6d
Peer Reviews Due :milestone, prm, 2026-07-30, 0d
section Final Deliverables
Final Report Writing :f1, 2026-06-30, 27d
Final Report Due :milestone, fm, 2026-07-27, 0d
Final Project Grading :milestone, gm, 2026-08-06, 0d
Grading
Grade Breakdown
Weights below are the split within your Final Project grade.
Make sure you pattern your Literature Review on those you see in high quality peer-reviewed research papers (you need 20+ citations). For an excellent example, see Burnam et al. (2014).
Have at least 20 peer-reviewed journal article citations.
Your group's analysis must use at least 3 datasets from 3 different data sources, joined together, with at least one dataset having 10,000+ rows. See the data sources requirement for details.
Your group must analyze the data using 3 models, each a specific instance of an analysis, with 10+ predictors. A model is a specific instance of an analysis (e.g., MLR + Poisson + Logistic), not just a model family — see the Final Report guide for details.
Split your data into training, validation, and test sets (required). Fit your models and perform variable selection on the training and validation data, then report final performance metrics on the held-out test set.
We expect you to perform all the professional steps you learn in this class: EDA + outlier screening, GoF testing, variable selection, and attempt to fix data/model when appropriate.
Include graphics when they're useful. Everyone likes pretty pictures: appropriate context and utility is what makes them pretty in data analytical paper.