Time series analysis and forecasting using the multiple regression and Box-Jenkins approaches.

Statistical procedures for process control including CUSUM and Shewhart Control Charts, and lot-acceptance sampling.

Social, technological, commercial, marketing, and political implications of current and impending tends in E-Commerce.

Theory and design of business simulation experiments, development and use of computer simulation models, and analysis of data generated by computer simulation experiments.

Theory and practice of making decisions in an environment of uncertainty; development of skill in the assessment of preferences and probability distributions.

Strategic management and use of information systems in organizations.

Technology overview and principles of database design for business applications. Enterprise database administration and planning. Design exercises and projects using the latest database management systems software.

Calculus and classical optimization methods applied to problems in business and economic analysis; matrices, derivatives, and integrals in the analysis of both univariate and multivariate business and economic models.

Statistics and probability theory applied to problems of business and economic analysis.

Probability and statistics necessary for graduate study in economics and business administration; estimation, hypothesis testing, regression, analysis of variance, and nonparametric methods.

Decision models useful in business and economics; linear programming, sensitivity analysis and duality, network models, integer programming, dynamic programming, inventory and queuing, and simulation.

Introduction to data processing concepts suitable for research interests in business and economics. Topics include research databases, statistical packages, and communication networks.

Quantitative procedures used to make informed business decisions. The course focuses on the application of descriptive statistics, probability, interval estimates, hypothesis testing, and regression to management problems. Restricted to business students.

The graduate-level course on Predictive Analytics using No-Code AI is designed to equip students with the necessary skills to apply advanced predictive analytics without the need for traditional programming.

This course covers skills necessary to pursue sourcing and related careers in manufacturing, services, retailing, and government agencies, including discussion of cutting-edge negotiation and sourcing strategies pursued by exemplar firms.

Management of projects including justification, planning, scheduling, monitoring, controlling, and auditing. Makes extensive use of project management information systems.

This course explores how operations managers can analyze and make decisions regarding the interaction of operations activities on the environment. Students will learn various tools to enable better decision making within the sustainable operations realm.

Study of the issues, principles, tools and decision processes involved in designing and effectively managing a supply chain. The course entails analyzing and developing models on various topics such as inventory management, transportation, network design and planning, and supply chain coordination.

Practical applications of statistical, optimization, heuristic, simulation, and other quantitative techniques for analyzing problems of contemporary business interest in the areas of manufacturing, services, and supply chain management.

Concepts of forecasting demand, segmenting customers and allocating capacity or customizing proce offers to distinct customer segments to maximize profits.

Creation and launch of viable businesses, products, and services using innovation tournaments. Development of problem solving and design skills. Application to real hurdles in innovation and entrepreneurship.

Study of the concepts, tools and issues associated with analyzing and improving modern business processes including quality management, process control, systems and technologies for process support, and case studies.

Overview of data resource management, including database technology and design, information architecture planning, and database administration. A design project is required.

Survey of production or operations functions of organizations. Development of concepts and decision processes relevant to major problem areas. Emphasizes relevance of operations management in both manufacturing and service organizations.

Advanced theory and design of business simulation programs and validation and statistical analysis of model output.

Mathematical programming techniques which are useful in business and economics. Topics include: solution techniques and applications of linear programming, duality theory, parametric programming, the decomposition problem, integer programming, dynamic programming, Lagrange multipliers, Kuhn-Tucker theory, and an introduction to control theory.

A treatment of single equation estimating techniques for the simple linear model, various nonlinear models, and the general linear model.

The study of the integration of functional area and company-wide information components considering both internal and external information flows.

Statistical designs and techniques for survey investigations. Mathematical development of sampling systems; sampling units; sample size; estimation; costs; non-sampling problems. Methods of obtaining and reporting information.

Analysis of concepts, conventions, and assumptions needed to manage cybersecurity policy and strategy development. Covers nomenclature, primary threat vectors, various cybersecurity frameworks, and ethical dimensions of cybersecurity management.

Analysis of service operations, integrated about strategy, design, and delivery issues. Comparison of manufacturing and service operations, emphasizing consumer participation in the service process.

Development and implementation of productive operations strategy and its relation to the overall organizational strategy; particular attention is given to the interface between product and process technology.

Design and management of systems that coordinate information and material flows within and between firms in a supply chain. Addresses planning basics, system alternatives, and advanced value stream synchronization.

The development and application of advanced statistical methods to problems in business and economics. Topics include application of estimation and hypothesis testing in both univariate and multivariate cases.

A study of data structures and file management with specific attention to applied business problems. Special emphasis is placed on the structure and management of information for management decision-making systems.

Technological concepts and techniques applied in video, data, and voice communications. Topics include local area networks, wide area networks, standards, management, and cost issues involved in telecommunications.

The structure and analysis of experimental and research designs with applications to business and economic problems.

Topics will be selected from: nonlinear programming, stochastic programming, integer programming, spectral analysis, decision theory, Markov processes, Box-Jenkins methods, management information systems.

Topics in generalized least squares, autocorrelation, distributed lag models, principle components, identification, and simultaneous estimating techniques.

Selection, design, and application of a wide range of decision support systems and knowledge-based information technologies for supporting effective managerial decision making.

This course entails a live project under faculty supervision in which student teams apply GSCOM concepts and techniques to solve practical significant problems and opportunities in real-world service and manufacturing firms.

The role of product and process innovation in competitiveness, intellectual property rights, organizing the technical effort, and techniques to enhance and pace technology development.