Module POLM809 for 2019/0
- Overview
- Aims and Learning Outcomes
- Module Content
- Indicative Reading List
- Assessment
Postgraduate Module Descriptor
POLM809: Applied Quantitative Data Analysis
This module descriptor refers to the 2019/0 academic year.
Module Aims
POLM809 intends to provide an advanced introduction into quantitative methods in the social sciences. You will acquire skills to analyse data in various forms and using a variety of quantitative tools, techniques and software packages. You will learn the strengths and weaknesses of various techniques and be taught how to deal with issues such as missing data and data bias. By the end of a course of practical demonstrations, associated lectures, and practical assignments, this module aims to have enhanced your skills in the analysis and presentation of quantitative data appropriate to a wide range of research problems. Throughout the module, emphasis will be placed on applying the techniques learned and the practical experience of analysing quantitative data sets. You will learn how to construct data sets from individual and aggregate level data, how to describe and visualize relevant data patterns using graphical tools, how to analyse the data using the appropriate statistical tools, and how to interpret the results of this analysis. You will focus on the analysis of questionnaires, historical data, content analysis and other data sources. Examples will be drawn from the humanities and social sciences
| On successfully completing the programme you will be able to: | |
|---|---|
| Module-Specific Skills | 1. recognize and evaluate in writing the diversity of specialized techniques and approaches involved in analysing research information, both quantitative and qualitative; 2. critically evaluate in writing the issues involved in application of research design in the context of the social sciences; 3. Demonstrate acquired skills in data analysis 4. demonstrate acquired skills in a computer package for statistical analysis (e.g. SPSS, Stata); 5. Show ability to present analysed data in a coherent and effective manner. |
| Discipline-Specific Skills | 6. demonstrate understanding in the use of advanced tools and techniques of quantitative research; 7. construct well thought out and rigorous data analysis, tables and reports for both written and oral presentation; 8. examine relationships between complex theoretical concepts with real world, empirical data; |
| Personal and Key Skills | 9. demonstrate an advanced ability to study independently and effectively; 10. deliver accurate and nuanced presentations to your peers, and communicate effectively in speech and writing; and 11. use IT for the retrieval and the presentation of a wide variety of information. |
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 |
|---|---|---|---|
| Performance in sessions | Weekly | 1-11 | 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 |
|---|---|---|---|---|
| 3 practical assignments (written), with exercises focusing on data analysis, visualization and interpretation | 75 | 500 words each (25% each) | 1-11 | Written feedback |
| Final assignment (written): Essay discussing how to use the tools and techniques covered during the module to address a relevant research question | 25 | 1,500 words | 1-11 | 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 |
|---|---|---|---|
| 3 practical assignments (written), with exercises focusing on data analysis, visualization and interpretation | 3 practical assignments (written), with exercises focusing on data analysis, visualization and interpretation | 1-11 | August/September reassessment period |
| Written assignment discussing how to use the tools and techniques covered during the module to address a relevant research question | Final assignment (1,500 words) | 1-11 | August/September reassessment period |
