Introduction to Quantitative Methods and Data Analysis I

The details
Colchester Campus
Postgraduate: Level 7
Thursday 03 October 2024
Friday 13 December 2024
23 April 2024


Requisites for this module



Key module for

MSC L25212 Conflict Resolution,
MSC L252EB Conflict Resolution,
MSC L252EK Conflict Resolution,
MSC L24012 Global and Comparative Politics,
MSC L240EB Global and Comparative Politics,
MSC L240EK Global and Comparative Politics,
MRESL25024 International Relations,
MSC L25012 International Relations,
MSC L250EB International Relations,
MSC L250EK International Relations,
MSC L20612 Political Economy,
MSC L206EB Political Economy,
MSC L206EK Political Economy,
MA L20012 Political Science,
MA L200EB Political Science,
MSC L20012 Political Science,
MSC L200EB Political Science,
MSC L20712 Public Opinion and Political Behaviour,
MSC L207EB Public Opinion and Political Behaviour,
MSC L207EK Public Opinion and Political Behaviour,
MRESL20024 Political Science,
MSC F7D412 Environmental Futures with Climate Change,
MSC L2P312 Politics, Communications and Data Analytics,
MSC L20812 Political Psychology,
MPHDL20148 Government,
PHD L20148 Government,
MPOLL234 Politics and International Relations,
MPOLL235 Politics and International Relations (Including Placement Year),
MPOLL236 Politics and International Relations (Including Year Abroad)

Module description

This module offers an introduction to the theory and practice of quantitative data analysis techniques. The goals are to provide students with the skills that are necessary to: 1) read, understand, and evaluate the academic literature, and 2) design and carry out simple studies that employ these techniques for testing substantive theories.

The module serves three principal purposes.

The first is to ground students in the language of social science research: research questions, independent and dependent variables, hypotheses, causality, etc. Students will come across these terms relentlessly in this module, in other modules, and throughout social science. It is thus important that they can identify them correctly in literature they consume and can come up with their own for independent research.

The second purpose is to introduce students to the types of data and the practice of data analysis in the social sciences. Students are introduced to a range of sources from which they can access quantitative data. Student will also be introduced to the programming language R, which is widely used by academics and practitioners for the analysis of quantitative data. I will assume that students have no prior experience with any of this software, and so students will be given a full introduction to its use.

The third purpose is to introduce a series of statistical techniques for the analysis of quantitative data. In this module, we will focus on describing data in various ways, both graphically and using statistical techniques. By the end of the module, we will cover the basics of linear regression.

Module aims

The aims of this module are to:

  1. Demonstrate the role of quantitative methods in answering research questions;

  2. Ground students in the language of quantitative research;

  3. Equip students with knowledge of a range of introductory statistical techniques;

  4. Develop students’ ability to interpret statistical information in substantive terms;

  5. Provide introductory training in the use of R;

  6. Show students how to locate and download existing datasets.

Module learning outcomes

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

  1. Read, understand, and evaluate basic quantitative analyses published in leading journals;

  2. Assess quantitative measurement in terms of reliability and validity;

  3. Understand the correct statistical method for particular research questions and variables;

  4. Use introductory statistical methods until linear regression with continuous dependent variables;

  5. Describe quantitative data with R, both statistically and visually.

Module information

No additional information available.

Learning and teaching methods

This module will be taught over 2 hours per week.



Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Online quiz 1    10% 
Coursework   Homework 1    20% 
Coursework   Online quiz 2    10% 
Coursework   Online quiz 3    10% 
Coursework   Homework 2    30% 
Coursework   Online quiz 4    20% 

Exam format definitions

  • Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
  • In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
  • In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
  • In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary, for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.

Your department will provide further guidance before your exams.

Overall assessment

Coursework Exam
100% 0%


Coursework Exam
100% 0%
Module supervisor and teaching staff
Dr Rabia Malik, email: rabia.malik@essex.ac.uk.
Dr Rabia Malik
Please contact govpgquery@essex.ac.uk



External examiner

Dr Kyriaki Nanou
Durham University
Associate Professor in European politics
Available via Moodle
No lecture recording information available for this module.


Further information

* Please note: due to differing publication schedules, items marked with an asterisk (*) base their information upon the previous academic year.

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