Module overview
The aim of this module is to present a range of data science concepts, including dealing with administrative and big data sources, and to present some basic methods for data analysis.
Aims and Objectives
Learning Outcomes
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- analyse simple unstructured datasets, and understand the challenges and risks of using standard analysis with these types of data
- write and use a simple web-scraping program
- search out and critically appraise the different types of data available for a particular task
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- Use basic data science approaches to answer analytical questions
- Undertake basic data manipulation in R
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- The data science approach to modelling and interpretation
Syllabus
- Data availability, data access, data law (compare and contrast different countries in Europe), consent.
- Administrative Data. Sources; modes of collection, compilation and storage; quality of administrative data. Uses of administrative data in official statistics. Case study.
- Exploratory data analysis
- Basic data analysis in data science paradigm, prediction focus, train-validate-test cycle, cross-validation
- Introduction to data visualisation.
- Big Data in Official Statistics, sources, access. Data quality, information content. Relationships and causality. Timeliness. Case study. Web scraping exercise.
Learning and Teaching
Teaching and learning methods
Depending on feasibility, teaching may be delivered face to face intensively over a week, or online using a mixture of synchronous and asynchronous online methods, which may include lectures, discussion boards, workshop activities, exercises, and videos. A range of resources will also be provided for further self-directed study.
| Type | Hours |
|---|---|
| Independent Study | 80 |
| Teaching | 20 |
| Total study time | 100 |
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Coursework | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Coursework | 100% |
Repeat Information
Repeat type: Internal & External