Description: Supervised statistical learning and multivariate analysis, concentrating on methods most often used in management science and finance. Topics selected from: multiple and multivariate regression; logistic regression; principal components and dimension reduction; discrimination and classification analysis; trees; partial least squares; nearest neighbor and regularized methods; support vector machines; boosting and bagging; and nonparametric regression. S+, SAS, or similar statistics package used for data analysis and data-mining.
Course #: 15.077
Professor(s) who recently taught this course:
Roy Welsch