Introduces the engineering student to the basic concepts of process model identification using experimental data. Various non-parametric methods as well as Time Series methods are covered. Dynamic Models identified are fitted to experimental data and are used for prediction and content. Computer packages are used extensively. Antirequisite(s): Prerequisite(s): Statistical Sciences 2141A/B or Statistical Sciences 2143A/B. Corequisite(s): Pre-or Corequisite(s): Extra Information: 3 lecture hours, 1 tutorial hour, 0.5 course. back to top
