GV900-7-FY-CO:
Political Explanation
2023/24
Government
Colchester Campus
Full Year
Postgraduate: Level 7
ReassessmentOnly
Thursday 05 October 2023
Friday 28 June 2024
30
17 February 2022
Requisites for this module
(none)
(none)
(none)
(none)
GV950
MA L24512 United States Politics
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
The above list is indicative of the essential reading for the course.
The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students.
Further reading can be obtained from this module's
reading list.
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 |
Homework 4 |
|
17.5% |
| Coursework |
Take home test |
|
30% |
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 Howard Liu, email: howard.liu@essex.ac.uk.
Dr Howard Liu
Module Supevisor Dr Howard Liu hl20840@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 958 hours, 0 (0%) hours available to students:
958 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).
Government
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