Data Analysis for Global Challenges (038IRS)
Data Analysis for Global Challenges
Module 038IRS
Module details for 2023/24.
30 credits
FHEQ Level 6
Module Outline
Ability to work with ‘large datasets’ is becoming a core skill in social science training and related career pathways. Focusing on key socioenvironmental challenges, this module offers a hands-on introduction to basic data analysis for students averse to numbers and statistics. You will learn where to access and how to use data on key social and environmental dynamics, how to examine the relation between different socio-environmental trends, how to analyse large textual data, how to read tables that report statistical results, and how to communicate/visualise the findings of your research. While working with socio-environmental data, you will deepen your understanding of the interaction between economic and environmental crises in the context of sustainability transition. This module is for students with no background in data or statistical analysis.
Module learning outcomes
Access, download and use large datasets to support or develop research ideas, projects and findings
Work with and analyse large textual data
Analyse key challenges to sustainability transition by utilizing different types of data (qualitative, quantitative, visual)
Use data visualisations (a) to identify patterns in, and draw insights from, complex data and (b) to communicate effectively research findings to different audiences
| Type | Timing | Weighting |
|---|---|---|
| Project (1100 words) | Semester 2 Assessment Week 1 Mon 16:00 | 30.00% |
| Coursework | 70.00% | |
| Coursework components. Weighted as shown below. | ||
| Project | T2 Week 6 | 35.71% |
| Project | T2 Week 9 | 35.72% |
| Group Presentation | T2 Week 11 (10 minutes) | 28.57% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Spring Semester | Workshop | 3 hours | 11111111111 |
| Spring Semester | Project | 3 hours | 00000100001 |
| Spring Semester | Workshop | 1 hour | 11111111111 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
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