DAT 385 - Forecasting

This course will build on students’ understanding of statistics and basic econometrics to develop further the empirical model building skills they have acquired previously. The course will provide an overview of classical and modern approaches to forecasting in business, economics, and finance. Topics include regression analysis, exponential smoothing and filtering, ARIMA models, modeling and forecasting trend and seasonality, evaluating and combining forecasts. Students will also write forecast reports and deliver oral presentations of their forecasts to classmates as well as learn how to critique constructively others’ reports and presentations.

Satisfies Data Science minor requirement.
Satisfiest Mathematical and Quantitative Thought requirement.

Prerequisites & Notes
An introductory statistics course equivalent to MAT 104/105 (e.g., BIO 240, ECO 204, POL 182, PSY 300, SOC 201).