This course introduces fundamental concepts and computations for statistical analysis of business data and real-world problems with an emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. The course covers basic descriptive statistical methods, sampling methodology, how to draw inferences from samples to larger populations and how to make predictions based upon historical relationships between variables.

This course introduces fundamental concepts and computations for statistical analysis of business data and real-world problems with an emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. The course covers basic descriptive statistical methods, sampling methodology, how to draw inferences from samples to larger populations and how to make predictions based upon historical relationships between variables.

Recent advances in the areas of productivity and quality improvement. Specific topics include all or some of: ISO 9000, Total Quality Management, Lean Thinking, Materials Requirements Planning (MRP), and miscellaneous techniques from Just-in-Time. If time permits, topics from one or more of the American Production and Inventory Control Society's (APICS) certification exams for the CPIM (the Operations Management counterpart to the CPA in accounting). Includes team field project at a local company.

Provides an introduction to project management, focusing on the integration of business operations and information management, and techniques to effectively manage the implementation of such projects.

This course introduces fundamental concepts and computations for statistical analysis of business data and real-world problems with an emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. The course covers basic descriptive statistical methods, sampling methodology, how to draw inferences from samples to larger populations and how to make predictions based upon historical relationships between variables.

Computer simulation presented for carrying out trial-and-error experiments on computer approximations of real, management systems. The goal is to 1) validate a new idea quickly, 2) diagnose potential product design problems, 3) optimize performance of complex systems, and 4) learn about something complex. The Arena environment, based on the SIMAN language, used to build models and video game-like animations.

This course introduces fundamental concepts and computations for statistical analysis of business data and real-world problems with an emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. The course covers basic descriptive statistical methods, sampling methodology, how to draw inferences from samples to larger populations and how to make predictions based upon historical relationships between variables.

Senior research, thesis option; by arrangement with a member of the department and the Honors Office.

This course exposes students to how core business concepts are implemented in real-world organizational settings. Key business processes covered include procurement (materials management), fulfillment (sales), and production (manufacturing). The class meets in a computer lab and enables hands-on experience, with instructor guidance, to the ERP solution from SAP, the world's largest business software company. Using the system's core modules and data warehouse, students will gain insight into online transaction processing (OLTP) and online analytical processing (OLAP).