Why was this course developed?
The Certificate in Statistics and Data Analysis was developed following a Scientific Skills Survey which was conducted by the Wales Ireland Network for Scientific Skills (WINSS) team to address the scientific skills gaps within industries based in Dublin, Meath, Kildare, Waterford, Kilkenny, Wexford, Wicklow, Carlow, South Tipperary, Cork and Kerry. The survey was sent to more than 100 companies in the pharmaceutical/biotechnology, medical device and food sectors. Transferable skills such as project management, data handling and analysis, statistics and IT skills are in high demand based on the response from 70% of the companies surveyed. Of the transferable skills listed, the skills most commonly required by the companies (84%) required training in the area of data handling and analysis. Recognising this demand, the Certificate in Statistics and Data Analysis was devised to provide advanced level training and address this skills deficit.
This course focuses on the application of modern data analysis techniques in the context of analytical method development. The course enables the student to apply statistical analysts processes to data sets, and to interpret the results in order to quantify data quality and compare data sets. Dedicated statistical software packages will be used for the delivery of this programme, features of which will enable the student to perform a comprehensive analysis and assessment of data quality. The student will learn to critically analyse analytical data using appropriate descriptive statistics tests, and to critically assess data sets based on applied inter-comparison significance tests. These data sets will deal with real world applications from the pharmaceutical, biopharmaceutical and food industries.
The student will also develop competence in a range of process control tools and minimisation strategies, and will learn to justify their usefulness to control a process. In addition, the student will learn to critically evaluate sampling plans and perform statistical analysis of quality in product batches. Continuous improvement and data-driven decisions will also be emphasised throughout the course.
What are the learning outcomes?
On successful completion of this module, a student will be able to:
- Critically analyse analytical data using appropriate descriptive statistics tests.
- Critically assess data sets based on applied inter-comparison significance tests.
- Critically analyse analytical data using statistical software packages.
- Synthesise and integrate process capability indices as a statistical measure of process capability.
- Justify the usefulness of Shewhart control charts, CUSUM charts and other control charts to control a process.
- Critically evaluate sampling plans and statistical analysis of quality in product batches.
How is this course delivered?
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The Certificate in Statistics and Data Analysis programme is taught using a block approach on a part-time basis to facilitate students in full-time employment.
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Since this course is also offered as one module of the two year MSc in Analytical Science with Quality Management programme, the Certificate in Statistics and Data Analysis is only offered once every two years.
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Over the duration of the programme, students will be required to attend SETU Waterford for approximately 8 days from January to June.
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This programme will be delivered through a blend of lectures, tutorial sessions and IT practicals, as well as independent study. Lectures will be used to introduce the concepts behind a range of data handling and analysis tools, and a variety of statistical tests. This material will be significantly expanded upon and developed through problem-solving, an approach that will be adopted during tutorial sessions. IT practicals will also be used to demonstrate how data analysis tools and dedicated statistical software packages can be used to evaluate relationships in scientific data.
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Continuous assessment will be carried out throughout the course of the programme.
The Certificate in Statistics and Data Analysis programme is aimed at those already working in the pharmaceutical, biopharmaceutical and food industries. This programme is also suitable for students intending to/already undertaking postgraduate research study.
Statisitcs and Data Analysis Entry Requirements
Applicants for entry to this programme should hold a Level 8 Bachelor’s degree at honours level minimum 2.2 in an appropriate subject area or equivalent qualification.
Applicants whose first language is not English must submit evidence of competency in English, please see SETU Waterford’s English Language Requirements for details.
How to Apply
Applications for this programme are made online by going to www.pac.ie
This course places a strong emphasis on the professional development of the graduate and is aimed at students already working in an industrial environment. Such a qualification will enable and facilitate career progression for graduates in the region.
Further study opportunities
This programme can be taken as a stand-alone Certificate worth 10 credits at level 9, or if the student wishes, they can use these credits towards the 60 credit Postgraduate Diploma in Analytical Science with Quality Management SE51H /SE51J or the 90 credit MSc in Analytical Science with Quality Management SE51H /SE51J
This course places a strong emphasis on the professional development of the graduate and is aimed at students already working in an industrial environment. Such a qualification will enable and facilitate career progression for graduates in the region.
Further study opportunities
This programme can be taken as a stand-alone Certificate worth 10 credits at level 9, or if the student wishes, they can use these credits towards the 60 credit Postgraduate Diploma in Analytical Science with Quality Management SE51H /SE51J or the 90 credit MSc in Analytical Science with Quality Management SE51H /SE51J
Stream Leaders
Dr Richie Ryan
Pharmaceutical Science Lecturer -
Call: +35351845509
Email: [email protected]
ProfileDr Mike Kinsella
Lecturer in Chemistry/Organic Chemistry & Researcher, PMBRC -
Email: [email protected]
Profile