Identifying Important Predictors for Academy Award Success - MATH 396 Undergraduate Research Project Application Form

Supervisor's Name: Masoud Asgharian

Supervisor's Email: masoud [at]

Supervisor's Phone: 5143981461

Supervisor's Website:

Supervisor's department: Mathematics and Statistics

Course number: MATH 396 (Mathematics and Statistics)

Term: Winter 2013-2014

Project start date: Monday, January 6, 2014

Project end date: Friday, April 11, 2014

Project title: Identifying Important Predictors for Academy Award Success

Project description (50-100 words suggested): Data collection, modelling and inference in order to predict the outcome of the Academy Award success. Using a sample size of the past 12 years of Oscar nominees and regressors such as past award performance, genre and gross earnings use multinomial logit models to predict the winners of the Academy Awards. Will deal with selection bias problem and model selection.

Prerequisite: 1 term completed at McGill + CGPA of 3.0 or higher; or permission of instructor.

Grading scheme (The final report must be worth at least 50% of final grade): 30% Mid-term Presentation; 70% Final Project report.

Project status: This project is taken. The professor has no more '396' projects this term.

Ethics, safety, and training: Supervisors are responsible for the ethics and safety compliance of undergraduate students. This project involves NEITHER animal subjects, nor human subjects, nor biohazardous substances, nor radioactive materials, nor handling chemicals, nor using lasers.