Department
Statistics and Data Science
Prof Chan Hock Peng
Head of Department (Previous)
Prof Chan Hock Peng
Head of Department (Previous)
Prof Adrian Roellin
Head of Department
w.e.f. 1 July 2021
Prof Adrian Roellin
Head of Department
w.e.f. 1 July 2021
Statistics and Data Science
Prof Adrian Roellin
W.E.F. 1 JULY 2021
Prof Chan Hock Peng
(Previous)
Shaping Future Talent
The Department of Statistics and Data Science is committed to furthering education and research in statistics and data analytics to support industry development and the growing manpower needs in these sectors. For instance, our existing undergraduate programmes in Statistics and Data Science and Analytics are continuously adapted in line with developments in science and industry. These two programmes were also redesigned to reflect the new College of Humanities and Sciences’ enhanced focus on quantitative reasoning in an interdisciplinary context by exposing students to real-world projects throughout their studies.
Cross-Disciplinary Programme
From this year onwards and together with the Department of Economics, Faculty of Arts and Social Sciences and Department of Mathematics, Faculty of Science, we will also offer the new Cross-Disciplinary Programme in Data Science and Economics. Apart from strong foundations in data science and economics, we place emphasis on students gaining experience in analysing economic data from financial markets, labour markets, education, health, housing and other areas. This will also help create awareness of the increasing impact data has on individuals, organisations, society and the global economic ecosystem.
Our successful Master of Science in Statistics programme has been enhanced with new applied components. This programme drew a record number of applicants, reflecting the recognition that a solid education in statistics, one of the foundational pillars of data science, remains key to the successful long-term integration of data into decision-making processes. The new cohort will have a capstone project as part of the programme to strengthen the practical aspects of data analysis.
In April 2021, we started to offer Continuing Education and Training courses under the SkillsFuture initiative. These full-day courses are available to the public as well as corporations to train their employees on the use of modern data analysis and visualisation techniques, and help enterprises unlock the potential of their otherwise overlooked data.
Shaping Future Solutions
Canonical Correlation Analysis has been one of the workhorses of statistics for many decades. The basic problem is to find relevant relations between two sets of variables, such as gene activation and deoxyribonucleic acid (DNA) methylation levels, which are involved in ageing and carcinogenesis. While traditionally, it is assumed that the amount of data surpasses the number of variables considered, this is often not the case in modern applications, where the expression levels of thousands of genes can be monitored simultaneously.
Prof ZHOU Wang has made important contributions to this field in the past years by using random matrix theory to understand the statistical behaviour of the empirical correlations in the data. His results help practitioners decide whether detected relationships between variables are real or spurious. For his significant contributions to probability theory and mathematical statistics, Prof Zhou was named a Fellow of the Institute of Mathematical Statistics (2021).
Fellow of the Institute of Mathematical Statistics (2021)
Department of Statistics and Data Science
Shaping Future Society
We continue to engage with existing and new government and industry partners through our Data Analytics Consulting Centre (DACC) and our sense-making modules, where students work in small teams on case studies provided by our partners.
For instance, DACC collaborates with Kantar Group through datathons, allowing us to explore new combinations of data, algorithms and solutions for transformational ideas. The development of recommendation systems is one example, where we look forward to create human-centric solutions that combine massive amounts of data and process it through new analytical engines. This enables us to provide meaningful advice to people on everyday challenges.
Two of our alumnae, Charmain TAN (Statistics, 2012) and CHUA Hui Xiang (Statistics and Management, 2012) were included in the inaugural list of SG100 Women in Tech (2020) awarded by the Singapore Computer Society. This accolade celebrates women who have made important contributions to technology in Singapore.
QuickDesk Pte Ltd
Dataiku