Course Catalog and Schedule



Marketing Models: Statistical Modeling (MKTG-552-0)
1.00 Credit
TCE BidStats

Description:
This is a doctoral course on statistical models suitable for Kellogg PhD students as well as PhD students from related fields such as statistics, economics, and engineering. The course is taught in the spring and topics alternate from year to year. Currently, in odd years the course is on Bayesian methods and computation and covers simple parametric models, regression models, hierarchical models, mixture models, optimization algorithms, Monte Carlo simulation algorithms, model checking, nonparametric models, and hidden Markov models while in even years the course is on applied and computational statistics and covers statistical graphics and exploratory data analysis, permutation tests, null tests, the bootstrap, smoothing, cross-validation, tree-based and linear regression, model selection, bagging, principal components analysis, and cluster analysis. Marketing applications include but are not limited to conjoint analysis, choice models, data minimization, perceptual maps, etc.

Prerequisites:
None

Download Schedule Information
Command item
  
Academic Year Term   Session Course ID Title Sec ID   Credits Syl Instructor Times Campus Location Mand 1st Exam
2014-2015 Spring 2015 10 Weeks MKTG-552-0 Marketing Models: Statistical Modeling 21 1 McShane, Blake Tue 1:00 PM - 4:00 PM Evanston Jacobs (488) N Check syllabus and confirm final deliverable or exam with professor.
2015-2016 Spring 2016 10 Weeks MKTG-552-0 Marketing Models: Statistical Modeling 21 1 McShane, Blake Tue 2:00 PM - 5:00 PM Evanston TBD (Room TBA) N