This module is designed to cover: Ethics and compliance of data science. Impact of international regulations. Appropriate handling of data. Simple random sampling. Sampling for proportions and percentages. Estimation of sample size. Stratified sampling. Systematic sampling. Cluster sampling. Data streams. Finding frequentist items. Estimating the number of distinct elements. Sparse recovery. Weight-based sampling. Real time analytics. Network data: Density, clustering coefficient, centrality and degree distribution.
Total contact hours: 40 hours
Private study hours: 110 hours
Total study hours: 150
Method of assessment
On successfully completing the level 6 module students will be able to:
1) demonstrate systematic understanding of key aspects of data collection and analytics;
2) demonstrate the capability to deploy established approaches accurately to analyse and solve problems using a reasonable level of skill in calculation and manipulation of the material in the following areas: sampling, questionnaire design, stream algorithms and network statistics;
3) apply key aspects of sampling, data stream models and network statistics in well-defined contexts, showing judgement in the selection and application of tools and techniques;
4) show judgement in the application of R and IT technologies in data collection and analytics.
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Credit level 6. Higher level module usually taken in Stage 3 of an undergraduate degree.
- ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
- The named convenor is the convenor for the current academic session.
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