Time Series Forecasting

1.5 Credits · Level: Undergraduate

Business forecasting refers to the tools and techniques used to predict developments in business and management such as sales, expenditures, and profits. The purpose of business forecasting is to develop better business and management strategies based on informed predictions. Virtually every manager has to make decisions or plans that depend on forecasts. With the rising interest in data-driven decision making, statistical forecasting methods have become the main and standard tools to make effective forecasts in business applications. This course builds upon the basic forecasting models studied in the introductory statistics core class. The aim is to further develop statistical modeling skills for business applications, with particular emphasis on time series, which form the inputs for sales forecasting and production planning as well as much financial and economic activity. Through examining time series, we can identify trends and patterns that enable us to make forecasts and to ascribe to those forecasts an adequate measure of the uncertainty surrounding the forecasts. The course will focus primarily on quantitative methods for forecasting, ranging from purely extrapolative approaches to causal modeling and topics such as exponential smoothing, ARMA/ARIMA models and seasonality.