Forecasting and Time Series Prediction
Forecasting is an integral part of decision-making activities. Organizations define goals, seek to predict environmental factors, and then take actions that they hope will result in the achievement of these goals. Forecasting allows organizations to decrease their dependence on chance and become more scientific in dealing with their environments. Today, forecasting rests on solid theoretical foundations while also having a realistic, practical base that increases its relevance and usefulness to organizations.
This course covers the full range of major forecasting methods, provide a complete description of their essential characteristics and presents the steps needed for their practical application, while avoiding getting bogged down in the theoretical details that are not essential to understanding how the various methods work. It provides a systematic comparison of the advantages and disadvantages of various methods so that the most appropriate method can be selected for each forecasting situation.
The course consists of lectures explaining and discussing the relevant material. Learning will be enhanced by homework assignments that will consider several practical applications.
The teaching methodology would be problem based and would encourage students to continue to employ either R or SAS.
Instructor – Martha Essak
Course Outline – Class of 2018 (Updated November 8, 2017)
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