An introduction to methods of statistical and machine learning analytics for economic analysis. Tools relevant for both small and large data sets will be covered. Topics may include approaches to classification, dimension reduction strategies, and prediction models and tools. Includes: Experiential Learning Activity Prerequisite(s): ECON 2708 with a grade of C+ or higher; and ECON 3210 (or equivalent) with a grade of C+ or higher. Lectures three hours a week. [0.5 credits]
An introduction to methods of statistical and machine learning analytics for economic analysis. Tools relevant for both small and large data sets will be covered. Topics may include approaches to classification, dimension reduction strategies, and prediction models and tools. Includes: Experiential Learning Activity Prerequisite(s): ECON 2708 with a grade of C+ or higher; and ECON 3210 (or equivalent) with a grade of C+ or higher. Lectures three hours a week. [0.5 credits]
