GV900-7-FY-CO:
Political Explanation
2022/23
Government
Colchester Campus
Full Year
Postgraduate: Level 7
Current
Thursday 06 October 2022
Friday 30 June 2023
30
11 January 2023
Requisites for this module
(none)
(none)
(none)
(none)
GV950
MA L25212 Conflict Resolution,
MA L252EB Conflict Resolution,
MA L252EK Conflict Resolution,
MA L24012 Global and Comparative Politics,
MA L240EB Global and Comparative Politics,
MA L240EK Global and Comparative Politics,
MA L25012 International Relations,
MA L250EB International Relations,
MA L250EK International Relations,
MRESL25024 International Relations,
MA L20612 Political Economy,
MA L206EB Political Economy,
MA L206EK Political Economy,
MA L20012 Political Science,
MA L200EB Political Science,
MA L20712 Public Opinion and Political Behaviour,
MA L207EB Public Opinion and Political Behaviour,
MA L207EK Public Opinion and Political Behaviour,
MRESL20024 Political Science,
MA L24512 United States Politics,
MA F7D412 Environmental Futures with Climate Change,
MA L20812 Political Psychology,
MPOLL268 International Relations,
MPOLL269 International Relations (Including Placement Year),
MPOLL370 International Relations (Including Year Abroad),
MPOLL234 Politics and International Relations,
MPOLL235 Politics and International Relations (Including Placement Year),
MPOLL236 Politics and International Relations (Including Year Abroad)
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 relentlessly 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. 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 their use.
The third purpose is to introduce a series of statistical techniques for the analysis of quantitative data. Some of the techniques are fairly simple, while others (especially those covered in the final weeks of the module) are advanced. The good news is that as the work becomes more challenging, the relevance of the techniques to modern social science research becomes more apparent.
The purposes 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 statistical techniques;
4. Develop students` ability to interpret statistical information in substantive terms;
5. Develop students` ability to comment critically on their own and others` analyses;
6. Provide training in the use of the R program;
7. Show students how to build their own and to locate existing datasets.
By the end of the module students should be able to:
1. Read, understand, and evaluate quantitative analyses published in the 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 a range of statistical methods, from calculating means to various regression models;
5. Analyse quantitative data with R;
6. Build their own datasets, and to download and use existing datasets;
7. Embark on the more advanced training available to postgraduate students at Essex.
No additional information available.
This module will be taught over 2 hours per week
This module does not appear to have a published bibliography for this year.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Coursework |
Homework 1 |
|
17.5% |
| Coursework |
Homework 2 |
|
17.5% |
| Coursework |
Homework 3 |
|
17.5% |
| Coursework |
Take Home Test |
|
30% |
| Coursework |
Homework 4 |
|
17.5% |
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
Reassessment
Module supervisor and teaching staff
Dr Muhammad Hussain, email: m.mohsin.hussain@essex.ac.uk.
Dr Muhammad Mohsin Hussain
Module Supervisors: Dr Muhammad Mohsin Hussain mh23290@essex.ac.uk
Module Administrator Jamie Seakens govpgquery@essex.ac.uk
Yes
No
Yes
Dr Damien Bol
King's College London
Senior Lecturer
Available via Moodle
Of 82 hours, 40 (48.8%) hours available to students:
2 hours not recorded due to service coverage or fault;
40 hours not recorded due to opt-out by lecturer(s), module, or event type.
Government
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