GV903-7-AU-CO:
Quantitative Methods

The details
2023/24
Government
Colchester Campus
Autumn
Postgraduate: Level 7
Current
Thursday 05 October 2023
Friday 15 December 2023
15
13 April 2023

 

Requisites for this module
(none)
(none)
(none)
GV900

 

GV953

Key module for

MRESL25024 International Relations,
MRESL20624 Political Economy,
MRESL20024 Political Science,
MSC L16512 Quantitative International Development,
MSC L20912 Quantitative Political Science,
MSC L209EB Quantitative Political Science

Module description

This module presents quantitative methods essential to test hypotheses in political science. After introducing the statistical computing environment R and associated document preparation software tools as well as bivariate hypothesis testing, linear regression using ordinary least squares estimation is covered in depth as the workhorse model for statistical inference in political science. The second half of the module will cover extensions for temporal and multilevel data and introduce methods for causal inference.


All models and methods are approached substantively, mathematically, and computationally (using R), with applications to political science research questions. Throughout the module, students will also familiarise themselves with the interpretation and presentation of empirical evidence in political science. The module will be particularly useful for students who aim to pursue careers in academia or in research-intensive environments, for example think tanks, research-related government posts, data science, or survey analytics.

Module aims

The module will enable students to:



  • understand and apply the logic of hypothesis testing in a variety of political science contexts.

  • understand and interpret statistical analyses in published political science research.

  • master the mathematics behind ordinary least squares and related regression models.

  • translate theories into empirical models.

  • conduct their own basic regression analyses using empirical datasets, both manually and with software, commensurate with analyses published in political science journals.

  • assess the goodness of fit of empirical models.

  • estimate causal effects of treatment variables on outcomes.

  • effectively present quantitative results using R and modern document formats embedded in statistical software.

Module learning outcomes

By the end of this module, students will be expected to be able to:



  1. formulate theories in ways that are amenable to single and multiple hypothesis testing and be able to diagnose violations of basic assumptions.

  2. understand, and be able to improve upon, statistical analyses and their interpretations in political science journals.

  3. have practical experience with conducting high-quality quantitative political science research as well as with the implementation of basic regression models, both using ready-made functions/packages in R and manually/from scratch.

  4. master the mathematics and statistical theory underlying hypothesis testing, ordinary least squares, time series analysis, panel and multilevel models, and causal inference techniques.

  5. know how to handle complex data structures and implement appropriate models, including temporal and hierarchical dependence.

  6. confidently apply causal inference techniques to estimate treatment effects.

  7. present statistical results effectively.

Module information

Indicative contents:



  1. Introduction to Quantitative Methods and R

  2. Hypothesis testing

  3. Linear regression I: Linear regression with one/two regressors

  4. Linear regression II: Ordinary least squares with multiple regressors

  5. Linear regression III: Assumptions of linear regression

  6. Methods for panel and multilevel data

  7. Time series analysis

  8. Causal inference I: Experimental design

  9. Causal inference II: Difference in difference and regression discontinuity

  10. Causal inference III: Matching, instrumental variables, and synthetic controls

Learning and teaching methods

The module will be delivered via:

1hr lecture + 1hr class (PC lab)

Bibliography

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   Assignment 1  17/11/2023  50% 
Coursework   Assignment 2  22/12/2023  50% 

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%

Reassessment

Coursework Exam
100% 0%
Module supervisor and teaching staff

 

Availability
No
No
Yes

External examiner

Dr Damien Bol
King's College London
Senior Lecturer
Resources
Available via Moodle
Of 30 hours, 26 (86.7%) hours available to students:
4 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s), module, or event type.

 

Further information
Government

Disclaimer: The University makes every effort to ensure that this information on its Module Directory is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to programmes, modules, facilities or fees. Examples of such reasons might include a change of law or regulatory requirements, industrial action, lack of demand, departure of key personnel, change in government policy, or withdrawal/reduction of funding. Changes to modules may for example consist of variations to the content and method of delivery or assessment of modules and other services, to discontinue modules and other services and to merge or combine modules. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications and module directory.

The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.