Module POL1041 for 2018/9
- Overview
- Aims and Learning Outcomes
- Module Content
- Indicative Reading List
- Assessment
Undergraduate Module Descriptor
POL1041: Data Analysis in Social Science
This module descriptor refers to the 2018/9 academic year.
Module Content
Syllabus Plan
Whilst the module’s precise content may vary from year to year, it is envisaged that the syllabus will cover some or all of the following topics:
- Introduction to data analysis in the social sciences
- Creating data: conceptualization, operationalization, and measurement
- Describing data I: tables and figures
- Describing data II: descriptive “statistics”
- Correlation and dependence
- Randomness and probability
- Sampling and “sampling distributions”
- Statistical inference: confidence intervals
- Hypothesis testing: introduction
- Testing the difference between two means
- Using quantitative methods in politics, sociology and criminology: illustration and examples
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 |
|---|---|---|
| 26.5 | 123.5 | 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 | 16.5 | 11 x 1.5 hour sessions |
| Scheduled Learning and Teaching Activities | 10 | 10 x 1 hour computer lab sessions |
| Guided independent study | 50 | Writing up problem sets and completing lab assignments |
| Guided independent study | 45.5 | Reading and preparing for lectures and tutorials, and completing online quizzes |
| Guided independent study | 28 | Web-based activities to familiarise students with statistical software. |
Online Resources
This module has online resources available via ELE (the Exeter Learning Environment).
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.
Imai, Kosuke. 2016. A First Course in Quantitative Social Science. Princeton, NJ: Princeton University Press.
Argesti, Alan and Finlay, Barbara. 1997. Statistical Methods for the Social Sciences, 3rd edition. Upper
Saddle River, NJ: Prentice Hall.
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.
