GV300-6-FY-CO:
Advanced Quantitative Political Analysis

The details
2024/25
Government
Colchester Campus
Full Year
Undergraduate: Level 6
Current
Thursday 03 October 2024
Friday 27 June 2025
30
15 October 2024

 

Requisites for this module
GV207
(none)
(none)
(none)

 

(none)

Key module for

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),
BSC L222 Politics and International Relations,
BSC L223 Politics and International Relations (Including Year Abroad),
BSC L224 Politics and International Relations (Including Placement Year),
BSC LL25 Politics with Business,
BSC LL26 Politics with Business (Including Placement Year),
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 examines quantitative methods in political research and shows how different methods can be used to answer substantive questions about political phenomena. After an initial examination of some tools for statistical inference the rest of the rest term of this module focuses particularly on regression analysis.


Attention is paid to the potential problems of the classical regression model and solutions to these problems. In the second term, we focus on how to use these tools to answer substantive questions about politics. We pay specific attention to threats to causal inference and how research can be designed to overcome them.

Module aims

The aims of the module are:



  • To understand the statistical ideas underpinning quantitative methods in political science research.

  • To evaluate the core assumptions of the classical regression model.

  • To understand the consequences for statistical inference when these assumptions are violated and to correct these violations in order to make valid inferences.

  • To explore issues of causal inference.

  • To understand how research design allows causal questions to be answered.

  • To employ a variety of functionality of standard statistical software (Stata or R) in their research

Module learning outcomes

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



  1. Advanced knowledge of descriptive and inferential statistics.

  2. Knowledge required to understand the assumptions underlying a broad range of basic and advanced statistical models used in social sciences.

  3. Understanding how advanced statistical techniques can be used to answer substantive research questions in political science.

  4. Foundations for undertaking work involving the statistical modelling of political phenomena and the study of causal mechanism thereof.

  5. Key skills required for research employed in various professional settings.

Module information

This module is part of the Q-Step pathway. Q-Step is an award which you can gain simply by enrolling on specific modules and will signal to employers your capability in quantitative research. Learn more about the Q-Step pathway and enhance your degree now.

Learning and teaching methods

This module will be delivered via:

  • 2 hours per week

Bibliography

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  04/11/2024  15% 
Coursework   Homework 2  25/11/2024  15% 
Coursework   Homework 3  20/01/2025  20% 
Coursework   Homework 4  10/02/2025  15% 
Coursework   Homework 5  10/03/2025  15% 
Coursework   Homework 6  24/03/2025  20% 

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
Dr Ryan Bakker, email: r.bakker@essex.ac.uk.
Dr Lewis Eves, email: le24306@essex.ac.uk.
Dr Ryan Bakker, Dr Lewis Eves
Please contact govquery@essex.ac.uk

 

Availability
Yes
Yes
No

External examiner

Dr Max Gallop
University of Strathclyde
Senior Lecturer
Resources
Available via Moodle
Of 20 hours, 20 (100%) hours available to students:
0 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

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