• Understand the use of Regression Analysis in Decision Making, such as in Business Forecasting
• Understand the use of Optimization in Decision Making, such as in Portfolio Optimization
• Understand the use of Risk Analysis in Decision Making, such as in Financial Investment
• Understand the use of Decision Analysis in Decision Making, such as in Project Management
• Use package computer programs, widely used in industry, for Regression Analysis, Optimization, Decision Analysis and Risk Analysis
• On the overall, appreciate the implications of uncertainty in Decision Making and the need for flexible and robust solutions

.In the current competitive environment, it is important to understand the relationships between different business factors, to forecast trends, to appreciate the risks arising from management actions, and to optimize investment strategies. Decisions are often taken under considerable uncertainty and time pressure. Therefore, managers need to be able to grasp the range of uncertainty rapidly and make rational decisions, which are both flexible and robust. This course aims to enhance your ability to apply modern Business Analytics tools, based on Statistical Analysis and Optimization, to decision-making. It is a practical course, which uses computer software to illustrate how to apply the methodologies introduced. The course is multidisciplinary with links to accounting, economics, finance, marketing and operations management.

During the course, and through a practical approach, students will develop quantitative skills necessary for Decision Making, as well appreciate the implications of uncertainty in Decision Making and the need for flexible and robust solutions.

Wisniewski, M. (2009), Quantitative methods for decision makers, 5^th edn. FT Prentice Hall.

Albright, S.C., Winston, W.L. and Zappe, C. (2011), Data Analysis, Optimization, and Simulation Modeling (UK: Thomson Southwestern)