Statistical Learning
Durham
Paul College of Business&Econ :: Decision Sciences
Credits: 3.0
Term: Spring 2022 - E-term III (01/18/2022 - 03/11/2022)
Grade Mode: Letter Grading
Term: Spring 2022 - E-term III (01/18/2022 - 03/11/2022)
Grade Mode: Letter Grading
Class Size:
30
CRN: 54916
CRN: 54916
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. Prereq: DS 803.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: Burcu Eke Rubini
Times & Locations
Start Date | End Date | Days | Time | Location |
---|---|---|---|---|
1/18/2022 | 3/11/2022 | M | 5:40pm - 9:15pm | PBLANE 216 |