Topics covered include graphical techniques such as scatter plots, box plots, parallel coordinate plots and other graphical devices, re-expression and transformation of data, influence and leverage, dimensionality reduction methods such as projection pursuit. Emphasis on modeling and problem solving. STAT344 or MATH 351, or equivalent. A survey of probabilistic methods for solving decision problems under uncertainty. Probability review, reliability, queueing theory, inventory systems, Markov chain models and Markov decision processes, and discrete-event simulation are covered.
Emphasis is on modeling and problem solving.
Computer simulation as a scientific methodology in operations analysis, with emphasis on model development, implementation and analysis of results. Discrete-event models, specialized languages, experimental design and output statistics are covered. Extensive computational work is required. This course is designed to be the capstone course for both the Masters program in Operations Research and the capstone course for the certificate in computational modeling. The focus is on model development and implementation involved in the practice of operational modeling.