Prospective Students

PhD in Statistics

 

 

Updated 15 November 2024

Program Objective

This programme is designed to train and guide students for a research intensive career in the academia or industry. The aim is to train scholars who can do original innovative research in theory, methods, or applications.

 

Admission Requirements

We invite graduates with strong academic potential and a keen interest in research to join our research-based doctoral programs. PhD admission criteria encompass a robust academic background, a passionate interest in a research topic, and good character. The following information will be considered for a careful evidence-based assessment:

  1. A good GPA in a relevant bachelor’s or master’s degree. (Applicants should have an upper second class Honours degree or higher in Mathematics /Statistics or equivalent qualifications and the ability to pursue research in Statistics/Probability.)
  2. A well-crafted statement of purpose detailing research interests, career aspirations, and motivations for choosing our program.
  3. Letters of recommendation from academic or professional referees, offering valuable insights into the applicant’s qualifications and research potential.
  4. A comprehensive CV highlighting academic accomplishments and pertinent experience.
  5. Standardized test scores such as the GRE. 
  6. Publications or involvement in research projects.
  7. For non-native English speakers, proficiency is demonstrated through tests like TOEFL or IELTS*.

Items (1) to (4) are compulsory.

Items (5) to (7) are optional; however, do note that evidence of strong quantitative, verbal, and analytical skills through GRE scores, as well as indicators of research skills and experience will significantly strengthen your application. 

* The following guidelines are provided for applicants whose native language or medium of undergraduate instruction is not English and the minimum TOEFL score ranges for NUS: 

Paper-Based(PBT):580-600
Computer-Based(CBT):237-250 
Internet-Based (iBT): 85

For IELTS, the score should be 6 and above.  

Please note that the TOEFL/IELTS scores are valid for 2 years from the test date. If it has been more than two years since you last took the test, you must take it again to have the scores reported. 

For GRE scores, the minimum score for the GRE Verbal (V) and Quantitative (Q) sections is 320, and the minimum score the Analytical (A) section is 3.5. Please note that the GRE scores are valid for 5 years from the test date. 

PhD candidates will still need sit for the PhD Qualifying Examination (QE) – 2 written and 1 oral examination. The QE should be taken before the end of the fourth semester of their Graduate Programme. A second attempt may be taken no later than six months after the first, failed attempt. This applies to both full-time and part-time PhD candidates. Candidates who fail their PhD QE will graduate with a Master of Science degree.

 

 

Period of Candidature

The minimum period of candidature will be two academic years and the maximum will be five academic years, both counted from the date of the candidate’s admission to the programme.

 

Degree Requirements

 

Coursework Requirements

Complete a minimum of forty-two (42) units in total. 

Six (6) units consisting of the following-

Course: NG5001 Academic Communication for Graduate Researchers (Compulsory for PhD students admitted from Semester 1, AY 2022/23 onwards)

Course: NG5002 Research Ethics for Graduate Researchers (Compulsory for PhD students admitted from Semester 1, AY 2024/25 onwards)

&

Thirty-six (36) units consisting of the following-

i) 7 compulsory core courses:

ST6120 Graduate Seminar Course in Statistics (previously offered as ST5198)

ST6101 Advanced Statistical Theory (previously offered as ST5215)

ST6102 Advanced Statistical Theory II (previously offered as ST5224)

ST6103 Advanced Probability Theory (previously offered as ST5214)

ST6104 Statistical Models (previously offered as ST5223)

ST6105 Computational Statistics (previously offered as ST5222)

ST5227 Applied Statistical Learning

ii) Any other two (2) ST-coded graduate course from the courses offered by the Saw Swee Hock Professors in the Department of Statistics and Data Science, or the following list of ST-coded graduate courses:

ST5209X Analysis of Time Series Data

ST5211X Sampling from Finite Populations

ST5203 Design of Experiments for Product Design and Process Improvements

ST5210 Multivariate Data Analysis

ST5212 Survival Analysis

ST5213 Advanced Categorical Data Analysis

ST5218 Advanced Statistical Methods in Finance

ST5221 Probability and Stochastic Processes

ST5225 Statistical Analysis of Networks

ST5226 Spatial Statistics

ST5229 Deep Learning in Data Analytics

ST5290 Data Science Industry Project

Students may read up to two graduate-level courses from other departments (subject to approval). Students must obtain a satisfactory grade for the Graduate Seminar Course. In addition, the students must receive a minimum GPA of 3.50 (an average grade of at least B) for nine courses from the list of prescribed courses.

 

Thesis/Dissertation

Students must submit, through the supervisor(s) and the Head of Department, his/her thesis/dissertation for examination within the maximum period of candidature. The thesis/dissertation must be on a topic approved by the respective departments and must make some contribution to knowledge and not be a mere collation of existing materials. The thesis/dissertation must contain original work or critical interpretation worthy of publication.

 

     

     

    Application

    There are two intakes in every academic year – August and January.

    Intake

    All Applicants

    Semester 1 (August)

    15 November of the previous year

    Semester 2 (January)

    15 May of the previous year

    Applicants are advised to apply online through this URL: https://gradapp.nus.edu.sg/portal/app_manage

    Priority for NUS Research Scholarship will be given to PhD applicants. Application for the scholarship is self-contained in the application package. Please read the instructions carefully when filling out the form. Further information on the scheme is available at the here.

     

    Fees

    Tuition Fees (Per Annum)

    The annual tuition fees for different categories of government-subsidised graduate programmes are set out here. The substantial tuition subsidy from the Government of Singapore comes in the form of a MOE Subsidy which is administered by the Ministry of Education (MOE) and is offered to all admitted students up to the maximum course duration. Students need not apply for the MOE Subsidy if they are eligible. International Students reading a government-subsidised programme can apply for the Service Obligation Scheme to pay reduced, subsidised tuition fees. 

    For students admitted into a government-subsidised graduate research degree programme will pay subsidised fees throughout their candidature as the Ministry of Education (MOE) will subsidise their tuition fees till their maximum candidature period and NUS will continue to subsidise the tuition fees for those who exceed the maximum candidature period.

    For updates on the fees payable and other financial matters, please click here.

     

    Scholarship & Stipend

    The scholarship includes a full tuition fee subsidy, which is in the form of credit towards student’s fee bill when the fee is due. Further information on the scholarship is available at https://nusgs.nus.edu.sg/scholarships/ .  In addition, our department provides additional top-ups to the scholars. For more information, please contact Ms Yang Qijun at qijun.y@nus.edu.sg

     

    Mandatory Miscellaneous Fees

    Miscellaneous fees are typically levied on items that are either not covered or partially covered by tuition fee and grant/subsidy. All students, whether registered on a full-time or part-time basis, are charged the mandatory miscellaneous fees. These are due at the same time as the tuition fees. These fees fall into the following general categories – registration, student activity, health service and insurance, and academic-related – and contribute towards defraying the associated costs. Annual miscellaneous fees payable are set out in here

     

    Q & A

    Please click here

     

    Enquiries

    Please contact Ms Yang Qijun at stabox10@nus.edu.sg