MSc Data Science (Statistics)(online)

Year 2

(Award available for year: Master of Science)

Learning outcomes

On completion of the MSc programme students should have provided evidence of being able to:

1) Demonstrate thorough understanding of the theory and application of key statistical methods and be able to implement them.
2) Demonstrate thorough understanding of some specialised topics in statistics.
3) Apply statistical methods in well-defined contexts, showing judgement in the selection and application of tools and techniques.
4) Demonstrate through completion of a project appropriate transferable skills and the ability to work under guidance.
5) Apply key programming skills in data analysis.
6) Describe, perform and critically evaluate a range of strategies for analysing data, selecting suitable strategies for specific problems and communicating the appropriate results in a relevant way.
7) Understand the difference of approach required between a traditional “simple random sample” and a “big data” (population) dataset and use this knowledge in devising analysis strategies.
8) Analyse large datasets, including those which have more variables than observations.
9) Describe issues associated with ethics and data governance and evaluate their impact on data gathering and analysis.

Transferable (key) skills

MSc students will have had the opportunity to acquire the following abilities through the modules specified for the programme:

- the skills necessary for employment in a higher capacity in industry or area of professional practice;
- the ability to reflect of individual achievements and learn from experience;
- self direction and effective decision making in complex and unpredictable situations;
- evaluating the quality of data and selecting suitable methods of analysis;
- interpreting data and making decisions based on that interpretation;
- setting targets for project work under supervision;
- independent learning and the ability to work in a way that ensures continuing professional development.

Assessment

Achievement for the MSc degree will be assessed by a variety of methods in accordance with the learning outcomes of the modules specified for the programme and will involve the achievement of the students in:

- evidencing an ability to select and conduct appropriate data analyses;
- demonstrating the ability to apply breadth and/or depth of knowledge to analysing data;
- drawing an analytic perspective on a particular area of study;
- make reasoned judgements whilst understanding the limitations on judgements made in the absence of complete data.

Assessment will take a variety of forms as appropriate to each module in the programme, both summative and formative.