Statistics
Those holding the Higher Diploma are deemed to have reached the honours degree standard in Statistics; it is awarded at pass and honours levels. Those holding the Diploma with a First Class Honours or with Second Class Honours Grade 1 are deemed ready for higher postgraduate research work in Statistics or related fields.
Students considering taking this course with a view to teaching Mathematics are strongly advised to talk to the Teaching Council in advance.
This is a one-year full time course, though it may be taken part time over two or more years.
Subjects taught
Course Structure
Modules include data analysis, research projects, linear models, categorical data analysis and statistical inference.
Entry requirements
The minimum requirement for entry to the Higher Diploma in Statistics is a primary degree in which Mathematics formed a substantial component. This includes degrees such as Mathematical Studies, Computer Science, or Education (with three years of Mathematics). Some prior exposure to Statistics is highly desirable. Applicants must have a recognised primary degree which is considered equivalent to Irish university primary degree level.
Minimum English language requirements:
•IELTS: 6.5 minimum overall score
•TOEFL (Paper based test): 585
•TOEFL (Internet based test): 95
•PTE (Pearson): 62
Maynooth University's TOEFL code is 8850
Application dates
All applications should be made through the PAC system.
Closing Date: 30 June 2021
Duration
1 year full-time, 2 years part-time
Fees
In general, there are two levels of fees payable. EU students from EU countries including Ireland pay a subsidised level of fees for both taught courses and research programmes. Tuition fees for students from outside the EU are not subsidised and are thus somewhat higher than for EU students.
Post Course Info
The course is suitable for those wishing to take up employment as a Statistician in areas such as the Civil Service, the Pharmaceutical sector, Banking and Finance, Insurance, Market Research, Environmental Monitoring, Industrial Quality Control, Statistical Programming and Data Management.