Course Catalogue

Advanced Regression: Limited and Categorical Dependent Variable Regression (M) SPS5075

  • Academic Session: 2026-27
  • School: School of Social and Political Sciences
  • Credits: 20
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No
  • Collaborative Online International Learning: No
  • Curriculum For Life: No

Short Description

Students will build on the techniques in introductory quantitative methods or the Semester 1 courses of the MSc Social Science Research Methods, to gain a more robust skill set to explore quantitative data using limited and categorical dependent variable regression analysis. The course will help students learn about advanced regression methods to examine differences and patterns of association with links to the school's thematic areas through using key dataset on topical areas such as: inequality, welfare, health, crime and conflict.

Timetable

10 x 2-hour lectures during a 10-week semester.

Tuesday 11am

10 x 1-hour workshop labs during a 10-week semester - lecturer-led.

Thursday 12pm

Requirements of Entry

Require introductory quantitative methods training t

Recommended: working knowledge of R (or similar statistical programming language e.g., Python, Julia)

Excluded Courses

SPS4004

Co-requisites

None

Assessment

Portfolio: 4,000 words total (100%, 4 labbooks (1,000 words each)).

 

Programme / course convenors and teaching staff will ensure that due consideration is given to students with disabilities, and that reasonable adjustments are implemented wherever possible, in consultation with relevant support services.

A Flexible Assessment approach will be applied, in line with Disability Service recommendations. This includes:

■ Consideration of alternative assessment formats where appropriate (e.g., adaptations to oral assessments)

■ Implementation of reasonable adjustments on a case-by-case basis

Course Aims

The aims of this course are as follow.

The course offers students a presentation of advanced quantitative methods to aid in examining the world around them and to serve as a stepping stone for future quantitative training. Based on through the course students will develop a critical view of data and statistics that can be applied to published information they are exposed to in their day-to-day lives and academia. Finally, the course especially its labs will equip students with quantitative and analytical skills to evaluate the data that they are exposed to, and to critically reflect on the impact of this data on social issues and policy formation.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ Identify when different quantitative techniques are appropriate and their limitations.

■ Analyse more advanced quantitative data analysis using tests of relationships on secondary data sets using R software.

■ Interpret statistical findings in writing, verbally, and graphically.

■ Show critical awareness of the production processes of a complete quantitative analysis of data.

■ Critically appraise material published within a relevant social science subject area.

Minimum Requirement for Award of Credits

No exceptions