Module Catalogue 2024/25

POL3055 : Applied Data Science for Political Research

POL3055 : Applied Data Science for Political Research

  • Offered for Year: 2024/25
  • Module Leader(s): Dr Sebastian Popa
  • Co-Module Leader: Dr Brian Boyle
  • Owning School: Geography, Politics & Sociology
  • Teaching Location: Newcastle City Campus

Your programme is made up of credits, the total differs on programme to programme.

Semester 1 Credit Value: 20
ECTS Credits: 0.0
European Credit Transfer System

Modules you must have done previously to study this module

Pre Requisite Comment

POL2017 or equivalent. Students should have previous knowledge with regards to formulating a good research question and hypothesis, and already be familiar with the techniques of collecting quantitative data.


Modules you need to take at the same time

Co Requisite Comment



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

Learning Outcomes

Intended Knowledge Outcomes

Upon successful completion of the module, students will be able to:
-       Understand key methodological and statistical concepts relevant to quantitative data analysis,
-       Demonstrate an ability to critically evaluate arguments supported by quantitative work,
-       Select and evaluate statistical tests appropriate to explore substantive research questions in the
fields of politics and international relations,
-       Enter, code, manipulate, and examine data sets with R (a free and popular software)
-       Formulate and test simple hypotheses using bivariate and multivariate designs.
-       Examine and evaluate different interpretations of political issues, events and solutions to problems
-       Describe, evaluate and apply different approaches involved in collecting, analysing and presenting
political information

Intended Skill Outcomes

Upon successful completion of this module students will be able to:
-       Demonstrate effective numeracy skills
-       Conduct quantitative data analysis
-       Use a popular and free statistical software
-       Conduct original research in politics
-       Develop reasoned arguments, synthesise relevant information and exercise critical judgement;

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion179:0079:00N/A
Structured Guided LearningLecture materials111:0011:00Pre-recorded lecture materials
Scheduled Learning And Teaching ActivitiesPractical112:0022:00PIP Computer labs
Structured Guided LearningStructured research and reading activities118:0088:00Guided coding tasks based on lecture content and reading in preparation for the computer labs
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.

Reading Lists

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Written exercise1M40Research assignment, written exercise - first half. 1500 words.
Written exercise1A60Research Assignment, Written exercise – Second half. 2000 words
Formative Assessments

Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.

Description Semester When Set Comment
Written Examination1MResearch assignment preparation, 500 word
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.


Past Exam Papers

General Notes


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The information contained within the Module Catalogue relates to the 2024 academic year.

In accordance with University Terms and Conditions, the University makes all reasonable efforts to deliver the modules as described.

Modules may be amended on an annual basis to take account of changing staff expertise, developments in the discipline, the requirements of external bodies and partners, and student feedback. Module information for the 2025/26 entry will be published here in early-April 2025. Queries about information in the Module Catalogue should in the first instance be addressed to your School Office.