Module POL3094 for 2019/0
- Overview
- Aims and Learning Outcomes
- Module Content
- Indicative Reading List
- Assessment
Undergraduate Module Descriptor
POL3094: Data Analysis in Social Science III
This module descriptor refers to the 2019/0 academic year.
Module Content
Syllabus Plan
Whilst the module’s precise content will vary from year to year, it is envisaged that the syllabus will cover some of the following themes:
- Data types and structures in R
- Data import with readr and data.table
- Data manipulation with dplyr
- Data visualisation with ggplot2
- Iteration
- Functions
- Reproducible research and effective presentation of statistical results
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 |
---|---|---|
22 | 128 | 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 & Teaching activities | 22 | 11 x 2 hour lectures / computer lab sessions |
Guided independent study | 78 | Reading and preparation for lectures and lab sessions |
Guided independent study | 50 | Reading, preparation and writing of the statistical report |
Online Resources
This module has online resources available via ELE (the Exeter Learning Environment).
“Data Analysis in Social Science 3”: http://abessudnov.net/dataanalysis3/
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.
Basic reading:
G.Grolemund, H.Wickham. R for Data Science. O’Reilly (2017).
P.Spector, Data Manipulation with R, Springer (2008).
A.Unwin, Graphical Data Analysis with R, CRC Press (2015).
N.Matloff, The Art of R Programming, No Starch Press (2011).
W.Chang, R Graphics Cookbook, O’Reilly (2013).