Introductory description

A vast amount of political research is quantitative, and even if you decide never to conduct quantitative analysis yourself, you will find an introductory level of knowledge in quantitative methods useful to critically engage with your discipline as a whole. Skills in data analysis are also crucial for finding employment in graduate level jobs; In a 2021 policy paper the Department for Science, Innovation and Technology found that amongst the top 10 skills UK businesses wish applicants to have, three are directly related to data analysis: Analysis Skills, Database Management, and Data Processing. This module will deliver an introduction to quantitative political analysis. It is based on Linke's typology of Quantitative Methods, and explores each of its tasks (conceptualisation and measurement, numerical data, data analysis and interpretation) at an introductory level. The module uses the software R.

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

1. Appointment with Evidence: Using the Power of Numbers
2. How to turn a Concept into a Number
3. Conceptualisation and Measurement in Practice
4. Understanding Single Variables
5. Types and Shapes of Data
6. (Reading Week)
7. Working with Variation: Probability and Sampling
8. Measuring Uncertainty: Thinking in Intervals
9. From Sample to Population
10. Why Statistics Can Mislead: Errors and Power Explained

Learning outcomes

By the end of the module, students should be able to:

• Apply the tasks of Quantitative Methods to substantive politics research problems
• Understand the basic principles of conceptualisation and measurement in political science
• Analyse core descriptive statistics, by hand and through the software R
• Understand the principles and core issues of statistical inference

Indicative reading list

Reading lists can be found in Talis

Specific reading list for the module

Research element

Focus on research design overall, and the role of quantitative methods within it

Interdisciplinary

Examples from multiple disciplines of the social sciences

International

Data from around the world is used.

Subject specific skills

• Quantitative Research Design
• Basic proficiency in a statistical programme
• Process of Conceptualisation and Measurement and its relevance in political science research
• Calculation of descriptive statistics

Transferable skills

• Written communication skills
• Oral communication skills
• Problem-solving skills
• Skills in the use of information technology
• Skills of interpretation and the critical analysis of primary and secondary sources
• The ability to digest, retain and apply complex information and ideas
• Ability to conduct research and reference your work appropriately
• Time management skills and the ability to meet deadlines
• The ability to reflect critically on the extent and limitations of how and what you have learned, discovered and understood