Module POL3094 for 2018/9
- 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 2018/9 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/
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 |
|---|---|---|---|
| Formative statistical exercises in class | 6 exercises (about 15 minutes each) | 1-6 | Peer and tutor verbal feedback |
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 |
|---|---|---|---|---|
| 5 short data analysis assignments to be submitted on Github Classroom | 50 | Data analysis exercises, about 500 words each assignment | 1-6 | Written feedback provided on Github |
| Final statistical report | 50 | 2000 words | 1-6 | Written feedback |
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 |
|---|---|---|---|
| Final statistical report | Statistical report (2000 words) | 1-6 | August / September reassessment period |
| 5 short data analysis assignments | 5 short data analysis assignments | 1-6 | August / September reassessment period |
