Module SSI1006 for 2021/2
- Overview
- Aims and Learning Outcomes
- Module Content
- Indicative Reading List
- Assessment
Undergraduate Module Descriptor
SSI1006: Data Analysis in Social Science 1
This module descriptor refers to the 2021/2 academic year.
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 |
|---|---|---|---|
| Lab assignments | 8 statistical software-related activities to be complete during lab sessions | 1-10 | Written |
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 |
|---|---|---|---|---|
| Problem set | 40 | 1,500 words | 1-11 | Written |
| Data analysis essay | 50 | 2,500 words | 1-10 | Written |
| Online quizzes | 10 | 3-5 multiple choice questions each week X 10 | 1-11 | Written |
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 |
|---|---|---|---|
| Problem set | A data analysis exercise that reinforces lecture material, from data collection to hypothesis testing (1,500 words) | 1-10 | August/September reassessment period |
| Data analysis | A data analysis essay that demonstrates that ability to analyse and effectively communicate empirical information (2,500 words) | 1-10 | August/September reassessment period |
| Online quizzes | A quiz on key data analysis techniques that reinforce the material presented in lecture, tutorials, and the reading | 1-11 | August/September 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.
Argesti, Alan and Finlay, Barbara. 1997. Statistical Methods for the Social Sciences, 3rd edition. Upper Saddle River, NJ: Prentice Hall.
Ayres, Ian. 2007. Super Crunchers: How Anything can be Predicted. New York: Bantam Dell.
Dalgaard, Peter. 2002. Introductory Statistics with R. New York: Springer.
Dilnot, Andrew and Michael Blastland. 2007. The Tiger That Isn't: Seeing Through a World of Numbers. London: Profile Books Ltd.
Imai, K. 2016. A First Course in Quantitative Social Science. Princeton, NJ: Princeton University Press.
Pollock, P. 2012. The Essentials of Political Analysis. 4th ed. Washington: CQ Press.
