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Dr Pik Kun Liew COL.7.15

This course is available on the BSc in Actuarial Science, BSc in Actuarial Science (with a Placement Year) and BSc in Mathematics, Statistics and Business. This course is not available as an outside option nor to General Course students.

Students should have taken, or be taking concurrently, Elementary Statistical Theory (ST102).

Business analytics is the process of using quantitative methods to learn from data to make informed business decisions. This half-unit course aims to provide students with an understanding of the context in which business analytics operates. Understanding the business environment and contemporary issues, such as the risks and impact of climate change, the fast-paced development of information technology and artificial intelligence, helps students to apply analytics concepts and incorporate these issues in decision-making effectively. Students will learn how business analytics assists organisations to make informed, confident decisions using statistical methods to create key metrics and to gain insights, reducing guesswork from decision-making. The course also aims to foster critical thinking regarding the complexities and intricacies inherent in data and statistical analysis. Students will learn about moral, data, and statistical literacy, along with the fundamentals of good statistical science. Students will be equipped with essential competencies to navigate ethical dilemmas, to obtain and handle data responsibly, and apply sound statistical principles in decision-making. It empowers them to be informed, ethical, responsible, and effective data practitioners.

The course takes an investigative and problem-driven approach and adopts the Problem, Plan, Data, Analysis and Conclusion (PPDAC) problem-solving cycle. Students will participate in project-based investigations, which serve as ideal platforms for student engagement, contextual problem-solving, and the integration of various learning components. These projects also provide a natural setting for developing statistical and critical thinking by guiding students through the entire process of conducting real statistical data inquiries—from initial conception and planning to data collection, exploration, and reporting. Additionally, collaborative group projects foster a dynamic learning environment, allowing students of all abilities to mutually enhance their knowledge and skills through interaction and share