MA Statistics
Graduate Taught (level 9 nfq, credits 120)

The goal of the MA Statistics is to train the new generation of data scientists, by empowering them with a broad range of skills in statistics and machine learning. Once completed, the MA Statistics brings students to the same level as the MSc Statistical Data Science: the degrees are equivalent. However, differently from the 1-year MSc Statistical Data Science, the MA Statistics is 16 months long, and it includes several fundamental statistics modules in its core structure. These modules cover the fundamentals of statistics and data science, and prepare students for more advanced modules.

The MA Statistics programme is aimed at students who have an undergraduate degree in a discipline with numerate skills, and who have covered some basic topics of statistics.

The MA Statistics is an EMOS (European Master in Official Statistics) labelled programme, which means that some students may have the opportunity to take modules and a project on official statistics, and potentially receive the EMOS certification of their degree. The EMOS MA Statistics also includes a research module, which is provided in the form of an internship at an institution whose work involves official statistics. The MA Statistics is the only EMOS accredited programme in Ireland and it is ideal for students that are interested in pursuing a career in official statistics, in Ireland or abroad.

The MA Statistics is ideal for students interested in data science careers in industry, business, government, and to those interested in pursuing a subsequent PhD in statistics or other areas related to data science.

Subjects taught

There are 120 credits of work to do spread over four semesters including nine 5-credit modules (45 credits) from the Higher Diploma programme

Students must take all Core modules in addition to the dissertation in order to complete the programme.

Stage 1 - Core
Technical CommunicationMEEN40670
Introduction to Bayesian AnalysisSTAT20180
Modern Regression AnalysisSTAT20230
Applied Statistical ModellingSTAT40510
Statistical Machine Learning (online)STAT40750

Stage 1 - Option
Numerical AlgorithmsACM40290
Data MiningCOMP40370
Machine Learning with PythonCOMP47750
Applied Matrix TheoryMATH40550
Advanced Predictive AnalyticsSTAT30250
Data Programming with RSTAT30340
Actuarial Statistics ISTAT40020
Actuarial Statistics IISTAT40070
Nonparametric StatisticsSTAT40080
Design of ExperimentsSTAT40110
Multivariate AnalysisSTAT40150
Survival ModelsSTAT40250
Monte Carlo InferenceSTAT40400
Stochastic ModelsSTAT40680
Time Series Analysis - Act AppSTAT40700
Data Prog with C (online)STAT40780
Data Prog with Python (online)STAT40800
Adv Data Prog with R (online)STAT40830
Data Prog with SAS (online)STAT40840
Adv Bayesian Analysis (online)STAT40950
Machine Learning & AI (online)STAT40970
Stat Network AnalysisSTAT41010
Bayesian Data AnalysisSTAT41070
Mathematical StatisticsSTAT41080

Entry requirements

- This programme is intended for applicants with a degree in Mathematics, Economics, Finance, certain Engineering degrees or similar quantitative disciplines where statistics has formed some component of the degree. An upper second class honours, or international equivalent is required.

- Applicants who do not meet these requirements but can demonstrate an interest and ability in statistics may be considered.

- Alternatively students may qualify for enrolment to the Higher Diploma Statistics from which they can gain entry to the 1-year MSc in Statistics.

- Applicants whose first language is not English must also demonstrate English language proficiency of IELTS 6.5 (no band less than 6.0 in each element), or equivalent.

These are the minimum entry requirements – additional criteria may be requested for some programmes

Application dates

How to apply?
The following entry routes are available:

MA Statistics FT (F043)
Duration 16 Months
Attend Full Time
Deadline Rolling*

MA Statistics PT (F044)
Duration 32 Months
Attend Part Time
Deadline Rolling*

* Courses will remain open until such time as all places have been filled, therefore early application is advised.

Who should apply?
Full Time option suitable for:

Domestic(EEA) applicants: Yes
International (Non EEA) applicants currently residing outside of the EEA Region. Yes

Part Time option suitable for:

Domestic(EEA) applicants: Yes
International (Non EEA) applicants currently residing outside of the EEA Region. No

This programme is intended for students with a numerate background but who may have insufficient background knowledge to gain entry to the MSc programme.




MA Statistics FT (F043): 16 months Full Time.
MA Statistics PT (F044): 32 months Part Time.
Mode of Delivery: Face-to-Face.


MA Statistics (F043) Full Time
EU fee per year - €10,235
non EU fee per year - €19,200

MA Statistics (F044) Part Time
EU fee per year - €3,610

***Fees are subject to change

Tuition fee information is available on the UCD Fees website. Please note that UCD offers a number of graduate scholarships for full-time, self-funding international students, holding an offer of a place on a UCD graduate degree programme. For further information please see International Scholarships.

Enrolment dates

Next Intake: 2024/2025 September.

Post Course Info

Careers & Employability
On successful completion of the programme, students will be able to demonstrate in-depth understanding of statistical concepts, apply advanced statistical reasoning, techniques and models in the analysis of real data, and employ technical computing skills.

Career opportunities exist in a variety of industries including pharmaceutical companies, banking, finance, government departments, risk management and the IT sector. Some past students embarked on a career in academia by proceeding to study for a PhD.

Graduates are currently working for companies such as Google, Western Union, AIB, Norbrook, Ernst & Young, Novartis, Deloitte, Meta and Eaton. Demand for our Statistics graduates continues to be strong both in Ireland and abroad.

More details
  • Qualification letters


  • Qualifications

    Degree - Masters (Level 9 NFQ)

  • Attendance type

    Full time,Part time,Daytime

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