Fundamental quantitative methods for business decision making: problem formulation, analysis, and use of management science tools, such as linear and integer programming, decision analysis and Monte Carlo simulation with spreadsheets. Extensive use of business applications.

This course is designed to provide students with an understanding of the behavior of individuals and groups in organizations. Students will identify and develop the skills needed to make an effective contribution to organization, to manage others, and to maintain a high quality of work life. Topics covered include: motivation, communication, conflict negotiation, group dynamics, leadership, organizational&job design, and change management

Topics will be announced when offered.

Topics will be announced when offered.

Topics will be announced when offered.

Statistical techniques in business data analysis; decision making under uncertainty. Concept of loss functions, decision trees, Bayes' Rule; correlation analysis, simple and multiple regression analysis (variable selection, model building, residual analysis); exponential smoothing methods; autoregressive (AR), moving average (MA), and ARMA models; introduction to intervention analysis, outlier-level shift-variance change detection procedures , and autoregressive conditional heteroscedasticity models. Extensive use of computer-based computational tools and business applications.

Topics will be announced when offered.

Topics will be announced when offered.

Topics will be announced when offered.