The Department of Statistics and Data Science at NUS is consistently ranked among the top Statistics departments in the world according to the QS World University Rankings. Part of our mission is to be a leader in education, and to train statisticians and data science professionals who can bring an understanding of data and evidence-based decision-making to the roles they will fill. Our MSc graduates find jobs in banking and finance, business and marketing, medical and health sciences, manufacturing and engineering, research and academic institutions, and in many other fields. Our exciting curriculum equips you both with fundamental knowledge in statistical theory and data science principles, as well as practical knowledge of specialized techniques in a wide range of areas in our elective courses. The MSc in Statistics is ideal for those looking to further their careers as industry statisticians or data scientists, or wanting a solid foundation for an entry into research.
We look forward to welcoming you to our programme!
Associate Professor David Nott (Programme Director)
NUS will adopt three new academic terminologies from 1 August 2023 – “Module” will be renamed “Course”, “Modular Credit (MC)” will be renamed “Unit”, and ‘Cumulative Average Point (CAP)” will be renamed “Grade Point Average (GPA)”. For more information, please click here (undergraduate) or here (graduate).
Updated 19 Nov 2024
Admissions Criteria
Application Period and Requirements
Early Admission Round (August AY2025 intake) – CLOSED
Application Period: 16 May 2024 to 15 July 2024
Due to high volume of applications, our graduate programme committee is screening through all the applications in batches. Applicants who are not shortlisted in the early admission round will be automatically rolled over to the regular admission round. All applicants will hear from us latest by June 2025.
Regular Admission Round (August AY2025 intake)
Application Period: 1 October 2024 to 31 January 2025
Instruction for Application:
The programme only has 1 intake per academic year in August.
Supporting documents:
Important Notes:
Application Outcome
Graduation Requirements
To graduate from the Programme, each candidate is required to read and pass five core courses, and five elective courses.
A minimum Grade Point Average (GPA) of 3.00 is required for graduation.
Candidature
This Programme is offered as a full time programme and a part time programme.
For full time students, the minimum and maximum periods of candidature are 1 year and 2 years for full time students. For part time students, the minimum and maximum periods of candidature are 2 years and 4 years.
Note: Most of the courses will be offered in the evening so that the Programme can be completed on a part-time basis.
Programme Structure
Please note the below information is for AY2022 intake and after.
The course list below may be updated rather regularly and subject to changes.
Core Courses — Students must complete all 5 Courses. (Total: 20 Units) |
|||
Course Code |
Course Title |
Units |
SSG-funded |
ST5201X |
Statistical Foundations of Data Science |
4 Units |
Χ |
ST5202X |
Applied Regression Analysis |
4 Units |
|
ST5209X |
Analysis of Time Series Data |
4 Units |
|
ST5211X |
Sampling from Finite Populations |
4 Units |
|
ST5188* |
Advanced Data Science Project |
4 Units |
|
Elective Courses – Students are required to complete any 5 courses. (Total: 20 Units) Up to two elective courses (8 Units) may be replaced by level 5000 courses from other departments, subject to approval from both departments. |
|||
Course Code |
Course Title |
Units |
SSG-funded# |
ST5203 |
Design of Experiments for Product Design and Process Improvements |
4 Units |
Χ |
ST5207 |
Nonparametric Regression |
4 Units |
Χ |
ST5210 |
Multivariate Data Analysis |
4 Units |
Pending |
ST5212 |
Survival Analysis |
4 Units |
√ |
ST5213 |
Advanced Categorical Data Analysis |
4 Units |
√ |
ST5218 |
Advanced Statistical Methods in Finance |
4 Units |
√ |
ST5221 |
Stochastic Processes and Applications |
4 Units |
√ |
ST5225 |
Statistical Analysis of Networks |
4 Units |
√ |
ST5226 |
Spatial Statistics |
4 Units |
√ |
ST5227 |
Applied Statistical Learning |
4 Units |
√ |
ST5229 |
Deep Learning in Data Analytics |
4 Units |
Χ |
ST5230 |
Applied Natural Language Processing |
4 Units |
Χ |
ST5290 |
Data Science Industry Project |
4 Units |
Χ |
* Students will be allowed to complete the ST5188 Advanced Data Science Project course entirely online only if it is their final course required for graduation from the programme.
# SSG funding for courses is limited in duration and subject to availability.
Fees
Application Fee:
Offer Acceptance Fee:
Tuition Fee:
Miscellaneous Student Fees:
The University reserves all rights to review fees as necessary and adjust accordingly without prior notice.
FAQ
1. I am interested in this programme but I do not have a degree in the area of statistics. Am I eligible to apply?
You are welcome to apply for the programme during the application period. All applications will be assessed based on relevant background knowledge and work experience with respect to the course. Applicants without a background in statistics but with sufficient knowledge to embark on the M.Sc. Statistics by Coursework programme may also be considered favourably.
2. I do not have an Honours degree (i.e. only 3-year Bachelor’s degree or its equivalent). Am I eligible to apply?
You are welcome to apply for the programme during the application period. Your application and relevant documents will be reviewed by our Admission Committee on a case-by-case basis.
3. Must I sit for TOEFL/IELTS test?
TOEFL or IELTS test ascertains a candidate’s English language proficiency and is necessary if English is not your native tongue and/or the medium of university instruction is not completely in English.
For details on test centres and test dates, please check the websites of TOEFL and IELTS.
4. I have been admitted to the programme but due to unforeseen circumstances, I may not be able to complete matriculation and commence study as planned. Can I defer my admission to the next intake?
If you have been offered a place in the programme and have paid the offer acceptance fee, you may request for deferment by sending us an email. Please note that all deferment requests are subject to approval by the department and faculty, and you will be notified of the outcome in due course.
5. I have been admitted to the programme but due to unforeseen circumstances, I have problems continuing with the programme. Can I withdraw from the programme?
If you wish to withdraw from the MSc Statistics coursework programme, you may do so by sending us an email stating your reasons. Please note that the offer acceptance fees or other fees payable for the programme are non-refundable and non-transferable. Kindly note that all withdrawal requests are subject to approval by the department and faculty, and you will be notified of the outcome in due course.
6. Are there any scholarships available for this programme?
There are currently no scholarships available for the programme. However, Singapore citizens and permanent residents are eligible for NUS rebates.
7. Am I eligible for staff concession if I am a full-time NUS staff member?
As this is a self-funded programme, students enrolled in our M.Sc. Statistics by Coursework programme will not be eligible for staff concession.
8. Am I eligible for the CPF Education Loan Scheme (CELS)?
Students enrolled in our M.Sc. Statistics by Coursework programme are not eligible for CPF Education Scheme (CELS) as it is only applicable to full-time undergraduate students. For more information, please visit the CPF website.
9. Am I eligible for the Post-Secondary Education Account (PSEA) scheme?
The PSEA Scheme is administered by the Ministry of Education (MOE) and is open to all eligible Singaporeans. Please refer to the MOE website to check your eligibility for PSEA.
For more information on using your PSEA funds to pay for tuition fees, please visit the NUS Graduate School’s website, available at this link.
10. I can’t find the answers in the FAQs above.
If you have any enquiries regarding our MSc in Statistics programme and cannot find the answers on our website, please feel free to email us with your full name in English. If you have already applied to the programme, kindly include your application number in the email subject line.