Quantitative Political Analysis

The details
Colchester Campus
Undergraduate: Level 5
Thursday 07 October 2021
Friday 17 December 2021
25 August 2021


Requisites for this module


GV300, GV508, SC208, SC385

Key module for

DIPLL20009 Politics,
BSC LL14 Economics and Politics (Including Foundation Year),
BSC LL2F Economics and Politics,
BSC LL3F Economics and Politics (Including Year Abroad),
BSC LL4F Economics and Politics (Including Placement Year),
BA L900 International Development,
BA L901 International Development (Including Year Abroad),
BA L902 International Development (Including Placement Year),
BA L921 International Development (Including Foundation Year),
BA L250 International Relations (Including Foundation Year),
BA L258 International Relations,
BA L259 International Relations (Including Year Abroad),
BA L260 International Relations (Including Placement Year),
MPOLL268 International Relations,
MPOLL269 International Relations (Including Placement Year),
MPOLL370 International Relations (Including Year Abroad),
BA LV21 Modern History and Politics,
BA LV22 Modern History and Politics (Including Placement Year),
BA LV28 Modern History and Politics (Including Foundation Year),
BA LV2C Modern History and Politics (Including Year Abroad),
BA L200 Politics,
BA L201 Politics (Including Year Abroad),
BA L202 Politics (Including Foundation Year),
BA L203 Politics (Including Placement Year),
BA L219 Politics with Human Rights (Including Placement Year),
BA L2M8 Politics with Human Rights (Including Foundation Year),
BA L2M9 Politics with Human Rights,
BA LFM9 Politics with Human Rights (Including Year Abroad),
BA L225 Politics and International Relations,
BA L226 Politics and International Relations (Including Year Abroad),
BA L227 Politics and International Relations (Including Placement Year),
BSC L222 Politics and International Relations,
BSC L223 Politics and International Relations (Including Year Abroad),
BSC L224 Politics and International Relations (Including Placement Year),
MPOLL234 Politics and International Relations,
MPOLL235 Politics and International Relations (Including Placement Year),
MPOLL236 Politics and International Relations (Including Year Abroad),
BA L215 Politics with Business,
BA L216 Politics with Business,
BA L217 Politics with Business (including Year Abroad),
BSC LL25 Politics with Business,
BSC LL26 Politics with Business,
BSC LL27 Politics with Business (including Year Abroad),
BSC LL20 Politics with Data Science,
BSC LL21 Politics with Data Science,
BSC LL22 Politics with Data Science

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 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 relentlesssly in this module, in other modules, and throughout social science. It is thus important that you are able to use them readily and correctly.
The second purpose is to familiarise yourself with 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. Students 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 their use.
The third purpose is to introduce a series of statistical techniques for the analysis of quantitative data.

Module aims

The purposes of this module are to: demonstrate the role of quantitative methods in answering research questions; ground students in the language of quantitative research; equip students with knowledge of a range of statistical techniques; develop students'; ability to interpret statistical information in substantive terms;
Develop students'; ability to comment critically on their own and others'; analyses; provide training in the use of the R program; show students how to build their own and to locate existing datasets.

Module learning outcomes

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

- read, understand, and evaluate quantitative analyses published in the leading journals;

- assess quantitative measurement in terms of reliability and validity;

- understand the correct statistical method for particular research questions and variables;

- use a range of statistical methods, from calculating means to various regression models;

- analyse quantitative data with R;

- build their own datasets, and to download and use existing datasets;

Module information

Students will require, use, and develop the following key skills:

- Critical thinking: students will consider the pros and cons of quantitative analysis and be able to evaluate their own and others'; research designs, measures and analyses;

- Transfer of ideas: students will be helped to follow and assess quantitative research in other modules: political behaviour, comparative politics, international relations, etc.;

- Use of statistical programs to analyse data: students will learn in lab sessions how to use the statistical programs R to analyse quantitative data;

- Improving independent learning and performance: Students will learn how they might think about and to address their own research topics in a quantitative framework;

- Communication and interaction: Both the lectures and lab sessions involve not only questions from the lecturer but also group discussions;

- Writing: Students learn how to report on and assess results of their quantitative analyses.

Learning and teaching methods

Each week we will have a recorded lecture and an in-person software demonstration. The software demo will also be streamed and recorded. Both the lectures and the demos will be available on Moodle.


This module does not appear to have any essential texts. To see non-essential items, please refer to the module's reading list.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Weighting
Coursework   Assignment 1   28/10/2021  10% 
Coursework   Assignment 2  18/11/2021  45% 
Coursework   Assignment 3  09/12/2021  45% 
Coursework   Assignment 4  23/12/2021  40% 

Overall assessment

Coursework Exam
100% 0%


Coursework Exam
100% 0%
Module supervisor and teaching staff
Dr Ryan Bakker, email: r.bakker@essex.ac.uk.
Dr Ryan Bakker
Module Supervisor: Dr Ryan Bakker -r.bakker@essex.ac.uk - Module Administrator: Lewis Olley - govquery@essex.ac.uk



External examiner

Dr Mohammed Rodwan Abouharb
University College London
Available via Moodle
Of 743 hours, 20 (2.7%) hours available to students:
723 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).


Further information

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