Advanced Quantitative Political Analysis
Undergraduate: Level 6
Thursday 06 October 2022
Friday 30 June 2023
22 May 2022
Requisites for this module
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
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.
The aims of the module are to:
1. understand the statistical ideas underpinning quantitative methods in political science research.
2. evaluate the core assumptions of the classical regression model.
3. understand the consequences for statistical inference when these assumptions are violated and to correct these violations in order to make valid inferences.
4. explore issues of causal inference.
5. understand how research design allows causal questions to be answered.
6. employ a variety of functionality of standard statistical software (Stata or R) in their research
On successful completion of the module, students should have:
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.
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
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.
Module supervisor and teaching staff
Dr Ryan Bakker, email: firstname.lastname@example.org.
Module Supervisor: Ryan Bakker email@example.com Module Administrator: firstname.lastname@example.org
No external examiner information available for this module.
Available via Moodle
Of 36 hours, 32 (88.9%) 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.
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