GV900-7-FY-CO:
Political Explanation

The details
2019/20
Government
Colchester Campus
Full Year
Postgraduate: Level 7
Current
Thursday 03 October 2019
Friday 26 June 2020
30
03 October 2019

 

Requisites for this module
(none)
(none)
(none)
(none)

 

GV903, GV906

Key module for

MA L25212 Conflict Resolution,
MA L252EK Conflict Resolution,
MSC L252EK Conflict Resolution,
MA L24012 Global and Comparative Politics,
MA L240EK Global and Comparative Politics,
MSC L240EK Global and Comparative Politics,
MA L25012 International Relations,
MA L250EK International Relations,
MRESL25024 International Relations,
MSC L250EK International Relations,
MA L20612 Political Economy,
MA L206EK Political Economy,
MSC L206EK Political Economy,
MA L20012 Political Science,
MA L20712 Public Opinion and Political Behaviour,
MA L207EK Public Opinion and Political Behaviour,
MSC L207EK Public Opinion and Political Behaviour,
MRESL20024 Political Science,
MA L24512 United States Politics

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 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.

Module aims

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.

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;
* embark on the more advanced training available to postgraduate students at Essex.

Module learning outcomes

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;
* embark on the more advanced training available to postgraduate students at Essex.

Module information

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.

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;
* embark on the more advanced training available to postgraduate students at Essex.

Learning and teaching methods

We have 4 hours each week allocated to the teaching of GV900. There will be a lecture session and each student also has to attend a practical session in the computer lab every week. The time and location of your practical session will be on your Online Timetable.

Bibliography

  • Huth, Paul; Croco, Sarah; Appel, Benjamin. (2012) 'Law and the Use of Force in World Politics: The Varied Effects of Law on the Exercise of Military Power in Territorial Disputes', in International Studies Quarterly. vol. 56 (1) , pp.17-31
  • Kellstedt, Paul M.; Whitten, Guy D. (©2018) The fundamentals of political science research, New York: Cambridge University Press.
  • Buhaug, Halvard; Cederman, Lars-Erik; Gleditsch, Kristian Skrede. (2014-06) 'Square Pegs in Round Holes: Inequalities, Grievances, and Civil War', in International Studies Quarterly. vol. 58 (2) , pp.418-431
  • David B. Carter and Curtis S. Signorino. (2010) 'Back to the Future: Modeling Time Dependence in Binary Data', in Political Analysis: Oxford University Press. vol. 18 (3) , pp.271-292
  • Beck, Nathaniel; Katz, Jonathan N.; Tucker, Richard. (1973-) 'Taking Time Seriously: Time-Series-Cross-Section Analysis with a Binary Dependent Variable', in American Journal of Political Science. vol. 42 (4) , pp.1260-1288
  • James A Piazza. (2011) 'Poverty, minority economic discrimination, and domestic terrorism', in Journal of Peace Research: Sage Publications, Ltd. vol. 48 (3) , pp.339-353
  • Lesley G. Terris and Zeev Maoz. (2005) 'Rational Mediation: A Theory and a Test', in Journal of Peace Research: Sage Publications, Ltd. vol. 42 (5) , pp.563-583
  • Garrett, Geoffrey; Mitchell, Deborah. (2001-03) 'Globalization, government spending and taxation in the OECD', in European Journal of Political Research. vol. 39 (2) , pp.145-177
  • Michael D Ward, Brian D Greenhill and Kristin M Bakke. (2010) 'The perils of policy by p-value: Predicting civil conflicts', in Journal of Peace Research: Sage Publications, Ltd. vol. 47 (4) , pp.363-375
  • Brambor, Thomas; Clark, William Roberts; Golder, Matt. (1989-) 'Understanding Interaction Models: Improving Empirical Analyses', in Political Analysis: Oxford University Press. vol. 14 (1) , pp.66-82
  • Maindonald, J.H. (2008) Using R for Data Analysis and Graphics: Introduction, Code and Commentary.
  • King, Gary. (1995-09) 'Replication, Replication', in PS: Political Science and Politics. vol. 28 (3) , pp.444-

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 Weighting
Coursework Homework 1 21/10/2019 15%
Coursework Homework 2 11/11/2019 15%
Coursework Homework 3 13/01/2020 15%
Coursework Homework 4 03/02/2020 15%
Coursework Homework 5 02/03/2020 15%
Coursework In-Class Test 24/04/2020 25%

Overall assessment

Coursework Exam
100% 0%

Reassessment

Coursework Exam
100% 0%
Module supervisor and teaching staff
Dr Ryan Bakker
Module Supervisor Professor Ryan Bakker r.bakker@essex.ac.uk or Module Administrator, Jamie Seakens (govpgquery@essex.ac.uk)

 

Availability
Yes
No
Yes

External examiner

Dr Nicholas Walter Vivyan
University of Durham
Senior Lecturer
Resources
Available via Moodle
Of 204 hours, 80 (39.2%) hours available to students:
124 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).

 

Further information
Government

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