# RESEARCH METHODS - 2018/9

Module code: POL2028

Module Overview

In this module we apply your knowledge of research theories introduced in POL2027 and engage with empirical research analysis. We will learn how quantitative and qualitative methodologies employed in political science can make use of database programs to store and handle both qualitative and quantitative information. We will also learn how statistics can be used selectively to mislead readers.

We will practice statistical skills, using R to test data, and design solid research projects that will require application of statistical analysis to test specific empirical hypotheses.

Module provider

Politics

NEZI Spyridoula (Politics)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 5

JACs code: X210

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

Module Availability

Semester 2

Prerequisites / Co-requisites

POL2027 Approaches to Research

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

• Introduction to empirical analysis databases: Excel, SPSS / R

• Descriptive statistical analysis (mean, mode, median, crosstabulations

• Mean comparisons, ANOVA analysis

• Correlations

• Linear regression (simple and multiple)

• Interpretation of results presented in graph or table format

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework R RESEARCH PROJECT 50
Examination 2 HOUR EXAMINATION 50

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:

·         R research project – 2000 words, 50% week 11

·         Exam – 2 hours, 4 questions to be selected from 8, 50%, exam period

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.

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 linear regression
• 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.

Learning outcomes

Attributes Developed
001 Engage in empirical research by gathering, organising and deploying evidence, data and information from secondary and primary sources. KCPT
002 Identify, investigate, analyse, formulate and suggest solutions to empirical political science problems. KCPT
003 Produce a rigorous research paper that contains statistical analysis of a political research question. KCPT
004 Produce and interpret tables, graphs and charts of empirical data using R PT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Independent Study Hours: 128

Lecture Hours: 11

Seminar Hours: 11

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 R sessions – 11 hours

• Seminars, using computer labs to practice R – 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.