Interpreting Geographical Data
| Code | School | Level | Credits | Semesters |
| GEOG1004 | Geography | 1 | 20 | Full Year UK |
- Code
- GEOG1004
- School
- Geography
- Level
- 1
- Credits
- 20
- Semesters
- Full Year UK
Summary
Quantitative data and analyses are important tools for studying physical and human phenomena in geography. The purpose of this core module is to familiarise students with basic statistical concepts and quantitative techniques that can be applied to the study of geography. Topics include summarising and interpreting quantitative data, study design, probability, distributions and confidence intervals, hypothesis testing, statistical inference and regression, and real-world applications. Data with geographical components will be drawn from diverse secondary sources and will be processed and analysed using a statistical software package.
Target Students
Only available to Year 1 students taking School of Geography undergraduate degrees.
Classes
This class will be taught through a mixture of interactive lectures and computing practical sessions. Drop-in sessions for extra-help will also be available.
Assessment
- 40% Coursework 1: 650 words Individual essay (AUT Sem)
- 20% In-Class Assessment: In-Class Assessment (SPR sem)
- 40% Group Project: 1500 words Group Project ( SPR Sem)
Assessed in both autumn & spring semest
Educational Aims
Upon completion of the module, the student should be able to • Demonstrate an understanding of the terminology, concepts, and principles of statistical concepts applicable to the study of geography• Summarise and describe quantitative data using charts and plots • Understand the development of a quantitative study design in geography • Apply hypothesis testing and statistical inference to explore questions in geography• Integrate quantitative data and tools to answer geography-related research questions.Learning Outcomes
• Knowledge: Comprehension of foundational terminology, concepts, and principles in statistics
• Critical thinking: Interpretation and evaluation of quantitative data to answer research-based questions in geography
• Practical skills: Proficiency in R (via RStudio) for quantitative data analysis
Practical skills: Proficiency software based quantitative data analysis