Aims

Quantitative methods are used across all areas of Politics and International Relations as one of the most common tools for bringing evidence and testing hypotheses. This module enables students to think about how to undertake political research focusing on the practical application of such methods. It also introduces useful practical and transferable skills, such as statistical analysis. Surveys and statistics in particular are emphasized in this module because they are often used for political purposes. Politics students need to understand how numbers are manipulated and used in politics. It is intended to enhance the quality of independent guided research, including in the project and dissertation modules, through ‘hands-on’ practical experience. Beyond the academic applicability of quantitative methods, the students will also gain enhanced transferable ICT skills such as learning how to use a free and powerful statistical software (R) popular among potential employers.

Outline Of Syllabus

Topics covered may include but are not limited to the following:
* Introduction to a quantitative method
* Data collection and data sources
* Univariate analysis of data (measures of central tendency, measures of distribution, z scores)
* Data visualization (winning arguments with numbers)
* Statistical inference and hypothesis testing (t-test)
* Bivariate analysis of data (scatter plots, cross-tabulations, measures of association, correlations)
* Linear and logistic regressions and their assumptions.
* Theoretical and substantive interpretation of statistical analyses

Teaching Rationale And Relationship

Pre-recorded lecture materials will impart basic information and background to undertake the practical skills sessions. They will introduce key concepts of quantitative research, place them within the context of epistemological debates and questions of research design and provide illustrations of applications to selected areas of quantitative study in politics research. Given the complexity of the material students might want to re-watch the lecture material multiple times, thus having access to quality bite-size recorded materials is preferable to PiP lectures.
In the practical sessions (PC lab sessions), students will have the opportunity to develop their proficiency in the use of statistical software. They will be based on the topics introduced in the lectures. During these sessions, students will have the chance to learn how to use statistical software to address and answer the research question that they will explore in their assessments.
Furthermore, they will provide the opportunity to discuss the application of quantitative methods, through reading of the work of established scholars and discussion of the students' own work from the computer labs.

Assessment Rationale And Relationship

The assessment has been broken into two parts, due to be submitted at different times in the term so that students have the opportunity to develop their skills and receive formative feedback. Each assessment component will consist of a series of guided tasks asking students to use the techniques taught to empirically investigate a research question. The students will have the chance to work on their proposals during the Practical sessions.

In the formative assessment, students should identify the data used to test their hypotheses as well as the variables they will use early in the semester. This will ensure that they can work on their own projects during the practical sessions.