GG4302 Data Science in Society and Space

Academic year

2025 to 2026 Semester 1

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

30

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 10

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Planned timetable

Fri 11am-2pm (practical) Wed 12-1

This information is given as indicative. Timetable may change at short notice depending on room availability.

Module coordinator

Dr C C Liu

Dr C C Liu
This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module Staff

Dr Chia Liu

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

Important questions related to social inequalities, health, and sustainability can often be addressed using existing data. This module focuses on developing quantitative skills by identifying appropriate methods using social statistics, and then interpreting, presenting, and analysing the data. Designed specifically for social scientists, the module equips students with the tools to effectively apply quantitative techniques and data visualisation to answer pressing social issues and communicate their findings through critical interpretation. This module is designed for students ready to engage in real-world applications of data analysis, with relevance to academia, industry, and beyond.

Relationship to other modules

Pre-requisites

BEFORE TAKING THIS MODULE YOU MUST PASS GG3206

Anti-requisites

YOU CANNOT TAKE THIS MODULE IF YOU PASS GG4223 OR TAKE GG4223

Assessment pattern

100% coursework

Re-assessment

100% coursework

Learning and teaching methods and delivery

Weekly contact

1-hour lecture + 1-hour seminar+ 3 hour practical (per 7 weeks)

Scheduled learning hours

40

The number of compulsory student:staff contact hours over the period of the module.

Guided independent study hours

265

The number of hours that students are expected to invest in independent study over the period of the module.

Intended learning outcomes

  • Demonstrate an understanding of the core quantitative research methodologies and a critical awareness of their strengths and weaknesses.
  • Interpret the results from these main quantitative modelling techniques.
  • Demonstrate critical understanding and practical research experience of a specific policy/ research area.
  • Use R to carry out multivariate modelling for a range of different outcomes
  • Demonstrate experience in working with multiple data sources and in the process of data preparation and cleaning.
  • Present quantitative research information in a variety of formats.