RESEARCH METHODS - 2023/4

Module Overview

This module will introduce students to quantitative research methods, with particular focus on current examples from politics building on POL2027 Approaches to Research. In this module students will be introduced to the basic concepts, methods, and techniques used in quantitative analysis and are necessary for understanding developments in politics and IR and decisions taken by the government and other public organisations. This module will also provide students with the skills necessary and the practical experience of using quantitative data and techniques of analysing it. This way students will learn new in-demand skills, not only for their studies but also skills they can highlight in their CVs.

The course uses the statistical software RStudio, and you will learn how to critical evaluate research questions by using them most important surveys available. Students will also learn skills they can apply at their dissertation and into assignments during the final year of their studies.

 

Module provider

Politics & International Relations

Module Leader

NEZI Roula (Politics)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 5

Module cap (Maximum number of students): N/A

Module Availability

Semester 2

Prerequisites / Co-requisites

POL2027 Approaches to Research SOC1025 or SOC1051 (Politics and Sociology)

Module content

Indicative content includes:

• Review of research methodologies employed in the study of politics


• Review of research question and hypotheses construction


• Hypothesis testing – descriptive and causal


• Variable operationalization and measurement


• The structure of a solid research project


• Descriptive statistical analysis (mean, mode, median)


• Bivariate hypothesis testing


• Correlations


• Linear regression (simple and multiple)


• Logistic regression


• Interpretation of results presented in graph or table format

Assessment pattern

Alternative Assessment

N/A

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate:

• The ability to select appropriate tests to explore a research question


• An engagement with the literature in their area of interest


• The ability to interpret statistics from published research and suggest alternatives


• An awareness of methodological suitability and potential weaknesses in their research design

Thus, the summative assessment for this module consists of:

• RStudio Exercises (25%)


• Research Project (75%)

Formative assessment and feedback

Verbal feedback in seminars, drop-in sessions for research projects, seminar tasks

Describe how students will receive feedback on their performance during the module such as verbal feedback in tutorials or a small assignment which informs the final summative assessment.

Research Project

Students are required to formulate a relevant empirical research question and hypotheses The completion of this assessment forms the basis for the future statistical assessments. For that purpose, students will have to:

I) Formulate a theoretically relevant empirical research question and describe the research hypotheses that would lead to testing it.

II) Establish and rationalise a clear causal relationship associated with the research question.

III) Identify: relevant literature, the variables involved in the model, causal relationships, data level, the most appropriate observational data; structure, the level of measurement of the variables included in the model.

IV) Include graphs and measures of central tendency (using RStudio) exploring the causal relationship identified in the research question. 

V) Conducting advanced statistical analysis using RStudio and reporting the results and conclusions. It will require bivariate and multivariate analysis of the causal relationship.

Assessment Criteria

Students will have to demonstrate a comprehensive understanding of the main principles of research design in Social Sciences and be able to successfully apply and describe the concepts covered during

the lectures to the research topic of their choice. Students will also have to demonstrate their ability to conduct independent quantitative research analysis using RStudio, and identify the appropriate statistical method to be used to answer specific research questions and interpret the results obtained.

Students will have to demonstrate their ability to conduct independent quantitative analysis using R Studio, identify the appropriate statistical method - bivariate and multivariate statistical analysis, to be used to answer specific research questions, interpret and visualise the results obtained.

 

Module aims

• Properly specify a research question related to a political puzzle;
• Link research questions to theoretical and societal debates demonstrating their contribution;
• Integrate theoretical literature to a research proposal;
• Propose testable hypotheses
• Think in terms of relationships between variables, including possible causal relationships;
• Gain competence in descriptive statistics and fundamental distributions
• Use statistical tools to conduct empirical analysis employing measures of association, mean comparisons, and regression analysis
• Produce written work that satisfies the criteria required in scientific publications, including proper citation and bibliographical references.
• Interpret and generate Tables, Charts, Graphs, to document empirical relationships are expected to participate and discuss the main concepts and studies from each section's readings.
• Be able to analyse complex problems and provide solutions through research with the use of data

Learning outcomes

Methods of Teaching / Learning

The learning and teaching strategy is designed to:

Provide students with statistical expertise and the ability to apply it to examining research questions

Encourage students to make their own choices in the employment of appropriate statistical tests

Enable students to choose a topic of their own interest, formulate a research question and test it

Introduce students to the expectations of statistical formatting

Encourage students to think creatively around a research problem

The learning and teaching methods include:

• Lectures, including interactive RStudio sessions – 11 hours


• Seminars, using computer labs to practice RStudio – 11 hours

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: POL2028

Programmes this module appears in

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2023/4 academic year.