This course aims to educate and to train students and other professionals in business, engineering, mathematics, economics, and statistics, to the principles and the methods for predicting, forecasting, and controlling, using probabilistic and statistical methods. It will start with an overview of methods for quantifying uncertainty, followed by methods of predicting binary outcomes. It will then discuss regression and time series based models, such as autoregressive-moving average processes, for predicting non-binary outcomes. This will be followed by a use of dynamic (or state-space/Kalman Filter) models for prediction and control. Theoretical underpinning will be emphasized and assignments will entail exercises as well as the analysis of data and/or the class participants.

Continuous Assessment: 40%

Examination: 60%

Examination Duration: 2 hours