Applied Statistics - Grangegorman

TU Dublin - Technological University Dublin

Applied Statistics - Grangegorman

What is... Statistics (Applied)?
The Postgraduate Certificate in Applied Statistics is a one-year part-time course, delivered by the School of Mathematics & Statistics. Classes are held in the evenings so that study can be balanced with work and personal life. This course studies a range of modern topics in statistics at Postgraduate Certificate level. The course is suitable for participants who wish to learn statistics for the first time or to build on their existing knowledge and skills set.

The course will be a blend of underlying theory and practice with an emphasis on the use of modern software packages, such as R. Participants will build on the skills required to understand the value and practical usage of statistical models, interpret and challenge results and have the ability to formulate and communicate the objectives of a statistical data analysis. Researchers who use statistical analysis and modelling techniques are also suitable for this course.

The programme Postgraduate Certificate in Applied Statistics comprises four taught modules. The course is associated with a student work load of 30 ECTS credits. All modules are core and learning is supported by the use of software, group learning, supported practical sessions, and the student library and study facilities.

Subjects taught

The following topics are covered in the taught modules:
• Introduction to Probability and Statistical Inference (10 ECTS credits)
• Statistical Programming and Applications (5 ECTS credits)
• Linear and Generalised Regression Models (7.5 ECTS credits)
• Topics in Applied Statistics (7.5 ECTS credits)

Entry requirements

Minimum Entry Requirements?
Students wishing to enrol should normally possess at least the equivalent of: EITHER a qualification in Mathematics at level 7 on the National Framework of Qualifications and at least one year of relevant subsequent experience in a statistical role or two years of subsequent experience in an applicable area; OR a qualification at level 8 on the National Framework of Qualifications in any area with sufficient experience of a numerate discipline.

The Recognition of Prior Learning (RPL) procedures of the Institute will be used in assessing applicants who have qualifications not placed on the National Framework of Qualifications.

Application dates

Applications for courses commencing in September 2024 will open in November 2023.

Assessment Info

Assessment

The modules are assessed by a combination of continuous assessment undertaken during the semester and written examinations. Some modules involve practical tasks and are based solely on continuous assessment throughout the semester.

Examinations for Semester I modules take place in January and examinations for Semester II modules take place immediately following the end of teaching in May. Reassessment takes place in August. Students are required to attend the Institute and be available for examinations.

Duration

1 year
Mode of Study: Part Time
Method of Delivery: Online

Schedule
Each module is delivered over one semester. Online lectures and tutorials are held in the evenings.

Monday (Online)
18:30 - 22:00

Wednesday (Online)
18:30 - 22:00

Enrolment dates

Commencement Date: September 2024

Post Course Info

What are my career opportunities?
The demand for statistical expertise has never been greater, brought about, in part, by the increase in the amount of data collected and analysed by organisations and also by the expectation on both the public and private sector for excellence in the area of metrics and intelligence-based decision making. Graduates of this programme will be ready to take up data analysis and data scientist roles in sectors such as finance, manufacturing and engineering, internet technology, healthcare, government and non-profit organisations.

More details
  • Qualification letters

    PgCert

  • Qualifications

    Postgraduate Certificate

  • Attendance type

    Evening,Part time

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    Course provider