Module SSIM906 for 2021/2
- Overview
- Aims and Learning Outcomes
- Module Content
- Indicative Reading List
- Assessment
Undergraduate Module Descriptor
SSIM906: Quantitative Dissertation
This module descriptor refers to the 2021/2 academic year.
Module Aims
To enable you to write an extended piece of independent writing, around a topic of your own choosing using some of the quantitative data-analytic tools you became acquainted with during the programme (e.g., methods for causal inference, Bayesian econometrics, network analysis, text-mining and analysis techniques), in communication with key experts in your chosen area. It will allow you to demonstrate depth and breadth of knowledge in a particular subject area of professional or intellectual interest. The dissertation will be a mark of your ability to express yourself in writing.
On successfully completing the programme you will be able to: | |
---|---|
Module-Specific Skills | 1. Demonstrate knowledge in depth of a specialised subject area (may include a specific statistical technique) 2. Design an individual research programme, incorporating appropriate quantitative social science research methods 3. Collate and analyse primary or secondary data related to a subject discipline from appropriate sources. |
Discipline-Specific Skills | 4. Assimilate and critically analyse data from an appropriate range of sources, from primary or secondary data sets 5. Develop cogent argument and apply appropriate statistical techniques 6. Communicate complex information and ideas effectively in writing. |
Personal and Key Skills | 7. Use IT for information retrieval and presentation. 8. Manage own work |
Module Content
Syllabus Plan
At least four supervision meetings per term. There is an initial meeting to plan the dissertation followed by three meetings to give academic guidance including specific feedback on draft work.
Learning and Teaching
This table provides an overview of how your hours of study for this module are allocated:
Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
---|---|---|
8 | 442 | 0 |
...and this table provides a more detailed breakdown of the hours allocated to various study activities:
Category | Hours of study time | Description |
---|---|---|
Scheduled Learning and Teaching Activities | 8 | 4 x 2hour supervision meetings |
Guided Independent Study | 135 | Reading the relevant substantive literature to be able to write your dissertation on your chosen topic |
Guided Independent Study | 135 | Reflecting on an drafting your research design and methodological approach |
Guided independent study | 90 | Gathering data for preliminary analyses |
Guided independent study | 82 | Acquiring additional experience with software and computing tools required to conduct your research |
Online Resources
This module has online resources available via ELE (the Exeter Learning Environment).
How this Module is Assessed
In the tables below, you will see reference to 'ILO's. An ILO is an Intended Learning Outcome - see Aims and Learning Outcomes for details of the ILOs for this module.
Formative Assessment
A formative assessment is designed to give you feedback on your understanding of the module content but it will not count towards your mark for the module.
Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
---|---|---|---|
One draft chapter of the dissertation, or a developed introduction. Whichever the candidate feels most useful to gain feedback on progress. | one chapter or introduction | 1-8 |
Summative Assessment
A summative assessment counts towards your mark for the module. The table below tells you what percentage of your mark will come from which type of assessment.
Coursework | Written exams | Practical exams |
---|---|---|
100 | 0 | 0 |
...and this table provides further details on the summative assessments for this module.
Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
---|---|---|---|---|
Dissertation | 100 | 15,000 words | 1-8 | Written Feedback |
0 | ||||
0 | ||||
0 | ||||
0 | ||||
0 |
Re-assessment
Re-assessment takes place when the summative assessment has not been completed by the original deadline, and the student has been allowed to refer or defer it to a later date (this only happens following certain criteria and is always subject to exam board approval). For obvious reasons, re-assessments cannot be the same as the original assessment and so these alternatives are set. In cases where the form of assessment is the same, the content will nevertheless be different.
Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
---|---|---|---|
Dissertation | Dissertation (15,000 words) | 1-8 | Next reassessment period |
Indicative Reading List
This reading list is indicative - i.e. it provides an idea of texts that may be useful to you on this module, but it is not considered to be a confirmed or compulsory reading list for this module.
G King, R Keohane and S Verba, Designing Social Inquiry (Princeton UP, 1994);
D Burton (ed), Research Training for Social Scientists: A Handbook for Postgraduate Researchers (Sage, 2000).
S. Jackman. Bayesian Analysis for the Social Sciences (Wiley, 2000).
W. Greene. Econometric Analysis (Pearson, 2012).
Angrist, J., and Pishke, S. Mostly Harmless Econometrics (Princeton University Press, 2009).
Gelman, Andrew, and Jennifer Hill. Data analysis using regression and multilevel/hierarchical models. Cambridge University Press, 2006.
Kosuke, I.. Quantitative Social Science: An Introduction. (Princeton University Press, 2017)
Wooldridge, J. Econometric Analysis of Cross-Section and Panel Data (2010, MIT University Press).
Subject-specific reading will varying according to research topic.