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The Department of Statistics was founded in 1982. Our primary mission is to provide a quality education and undertake cutting-edge research. In today's Information Age, statistics has become an indispensable tool in business, social studies, engineering, medicine, clinical studies, genetics and marketing. In order to meet the increasing demand for well-rounded statistics graduates, we offer undergraduate programmes in Statistics, Risk Management Science, and Quantitative Finance and Risk Management Science (jointly administered by the Department of Finance). We also offer postgraduate programmes for students who intend to become experts in the field.
The curriculum is designed to prepare students for careers in fields such as business, teaching and research. The curriculum covers the core of the subject and maintains a balance between theory and practice. Students are required to engage in workshops, case studies and projects under then supervision of teaching staff, so as to broaden their statistical knowledge base, to hone their practical skills and to gain experience in handling real-life problems. Students can choose to specialise in one of the three streams: Data Science and Business Statistics Stream, Statistical Science Stream, and Data Analytics Stream.
Our graduates readily find employment in business, insurance, banking and finance, information technology, Government and professional services. Positions include statisticians, research analysts, data analysts, traders, financial analysts, risk analysts, consultants, software engineers, programmers and teachers. Many of them now hold key positions in the civil service and in various private sectors. Some of our graduates continue their studies and pursue a higher degree in overseas and local universities.
LAM Ka Yu
Through studying statistics, I have been trained to think deeply and critically when attempting to understand a problem, and to analyse data, explore meaningful findings and present them in a well-organised manner. During my summer internship as a big data analyst at the ParaDM Co., Ltd (arranged by the Statistics Department of CUHK), I proposed a regression model design and a hypothesis test for predicting the reading priority of a list of shared documents, thus leading to more efficient business decision making. The review sessions with my supervisors also enabled me to express my thoughts and discussed opinions with professionals. I believe my experience in these two months will be extremely helpful in my future career.