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QS301 - Advanced Quantitative Methods

  • Module code: QS301
  • Module name: Advanced Quantitative Methods
  • Department: Centre for Interdisciplinary Methodologies
  • Credit: 30

Content and teaching | Assessment | Availability

Module content and teaching

Principal aims

This module introduces students to a selected set of advanced statistical methods that are commonly used in quantitative social research. A further aim is to familiarise students with the key issues in the craft of applied work so that they become careful, considered and thoughtful researchers in quantitative social sciences.

Principal learning outcomes

By the end of the course, students will understand the basic principles of the advanced statistical methods covered, appreciate the context in which the methods are best applied, and have had practical experience of applying these methods to real-world data, using Stata and/or R.

Timetabled teaching activities

Classes are typically scheduled to Fridays, 9:00-12:00 pm, starting week 1 (Timetabled Teaching Activities are not finalised until September).

Departmental link

Other essential notes

This is a core module, which is supported by funding from the Nuffield/ESRC/HEFCE as part of the Q-Step degrees in ‘Sociology and Quantitative Methods’ and ‘Politics, International Studies and Quantitative Methods.’ Prerequisite Modules: QS104, QS105, QS202, QS203

Module assessment

Assessment group Assessment name Percentage
30 CATS (Module code: QS301-30)
A (Assessed work only) Data Analysis Report 1 (3000 words) 50%
  Data Analysis Report 2 (3000 words) 50%

Module availability

This module is available on the following courses:

  • Undergraduate Sociology and Quantitative Methods (L311) - Year 3
  • Undergraduate Politics, International Studies and Quantitative Methods (M162) - Year 3
  • Undergraduate Politics, International Studies and Quantitative Methods (with Intercalated Year) (M167) - Year 4
Optional Core


  • BA in Law and Sociology (Qualifying Degree) (with Intercalated year) (ML35) - Year 5