The module will provide the statistical and computing skills required to undertake the subsequent MSc Data Science modules delivered by SMSAS. This will include subjects such as introductory probability and statistics (e.g., hypothesis testing), R programming including data visualisation, and linear regression for multiple variables. Employability skills such as report writing, production of slides using appropriate software, and presentation skills. Ethical implications will be discussed throughout.
Private Study: 170
Contact Hours: 30
Total: 200
Group report on data analysis – 40%
Following feedback provided on the report, preparation, and delivery of an individual presentation with slides and a Q&A session – 60%
Reassessment methods
100% coursework, repeating individual presentation with slides.
The most up to date reading list for each module can be found on the university's reading list pages.
The intended subject specific learning outcomes
On successfully completing the module students will be able to:
1) Demonstrate a comprehensive understanding of the relevant parts of probability theory and statistical techniques such as hypothesis testing and apply them systematically.
2) Use R, including a conceptual understanding of programming in that language, and an ability to apply data visualisation techniques.
3) Demonstrate a systematic understanding of methods such as linear regression for multiple variables and be able to apply them to original problems and unseen data sets.
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