This unit introduces students to both quantitative and qualitative methods and their applications to decision-making in business management. The unit covers data analysis techniques around data presentation and interpretation, estimation, sampling, hypothesis testing and regression analysis, but it also broadly discussed decision analysis and decision making under uncertainty.

Decision-making is one of the most important and challenging tasks that business managers must do. A correct decision is hard to make without an appropriate analysis of information available. This unit introduces basic analytical methods as essential tools used to assist decision-making in business management. Some real-world examples on how analytical methods can assist business managers in decision making are: making decisions under uncertainty, scenario analysis, forecasting market demand, sales revenue, profit and freight rates, monitoring product quality, and choosing the optimal combination of production inputs.

Depending on the tasks and information available, the methods vary considerably. A substantial part of this unit concerns the application of statistical methods to decision-making, but it also gravitates heavily around modern decision-making techniques based on quantitative methods. You will learn how to collect, process and analyse data in order to assist decision making. You will learn a lot on decisions under risk and the techniques to rank alternatives modelled as trees, tables and lotteries.

Because this unit discusses the use of analytical tools in business management, practical applications are the main focus, and learning progress is made through practical exercises. Most exercises require calculations with the use of computers, calculators or other computational tools. Having said this, what you really need to learn are the methods rather than calculation skills. While some may find this unit challenging, its knowledge is essential for the study of final year units such as Port and Terminal Management and Transport Research Project.