DS 805 (02) - Statistical Learning

Statistical Learning

Durham   Paul College of Business&Econ :: Decision Sciences
Credits: 3.0
Term: Spring 2024 - Term 3 (01/23/2024 - 03/15/2024)
Grade Mode: Letter Grading
Class Size:   16  
CRN: 56832
This course introduces students to statistical tools for modeling and identifying patterns in complex data sets. The goal of statistical learning is to develop predictions informed by data. Topics to be covered include Gaussian linear models, cross-validation techniques, penalized regression methods such as ridge and LASSO, nonlinear models, logistic regression, tree-based models including random forests, bagging, and boosting, and support vector machines. Application areas include Marketing (e.g., effectiveness of advertising and customer satisfaction), Financial Economics (valuation), and Operations Management (resource allocation). The course delivery will be a mix of lectures, readings/podcasts with discussion, and hands-on data analyses.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): DS 803
Instructors: Burcu Eke Rubini

Times & Locations

Start Date End Date Days Time Location
1/23/2024 3/15/2024 T 2:10pm - 5:30pm PCBE G45