Module POLM086 for 2021/2
- Overview
- Aims and Learning Outcomes
- Module Content
- Indicative Reading List
- Assessment
Postgraduate Module Descriptor
POLM086: Quantitative Data Analysis
This module descriptor refers to the 2021/2 academic year.
Module Aims
By the end of a course of practical demonstrations, associated lectures, and practical assignments, this module aims to have significantly developed your skills in the analysis and presentation of quantitative data appropriate to a range of research problems. There will be an emphasis placed upon 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. You will then learn how to analyse the data using the appropriate statistical tools. You will learn how to apply techniques in parametric and non-parametric inferential statistics, from simple t- tests for the comparison of means to more complex multivariate statistics, including linear multiple regression. You will also learn techniques for the visual display of data. There will be a brief introduction to analysis of categorical (eg binary) data, time series, and panel data to provide a route map for further independent study. You will focus on the analysis of different types of data including survey data and various sources of official data, and their associated problems for analysis
On successfully completing the programme you will be able to: | |
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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, confidence, and competence in data analysis; 4. demonstrate acquired skills. confidence and competence in a computer package for statistical analysis [e.g. SPSS] 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 and real world empirical data. |
Personal and Key Skills | 9. develop an advanced ability to study independently 10. deliver detailed and nuanced presentations to your peers, and communicate effectively in speech and writing 11. use IT for the retrieval and the presentation of information |
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: why use quantitative data and
Descriptive statistics, measures of central tendency, graphical presentation
Collecting data, sampling, data management and data integrity
Describing data, graphical presentation of data and dealing with missing data
Inferential statistics and research design
Comparing means
Testing relationships between variables
Multivariate statistics including ordinary least squares regression
Categorical data analysis including logit and probit models
Advanced techniques, including panel data, and paths for future study
Student Presentations
The module will be taught through 11 weekly two-hour sessions (including introductory session). There will be a mix of formal lectures led by the co-ordinator, practical experience, student presentations and student discussion. The emphasis is on active seminar participation, practical experience and the development of techniques and tools with regard to assessed work. The techniques will be explored through appropriate practical work and independent study.
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 | 278 | 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 | 22 | 11 x 2 hour sessions |
Guided independent study | 200 | Completion of assessment tasks |
Guided independent study | 78 | Preparation for seminars |
Online Resources
This module has online resources available via ELE (the Exeter Learning Environment).
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 |
---|---|---|---|
Individual presentation of data analysis problem, based on final project | 10 minutes | 10, 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 |
---|---|---|---|---|
Practical assignments + data analysis including results tables and graphs | 50 | 3 x 500 words | 1-9 | Written and or verbal feedback |
Final assignment + data analysis including results tables and graphs | 50 | 3,000 words | 9-11 | Written and or verbal 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 |
---|---|---|---|
Practical assignments + data analysis including results tables and graphs | Practical assignments + data analysis including results tables and graphs | 1-9 | August reassessment period |
Final assignment + data analysis including results tables and graphs | Final assignment + data analysis including results tables and graphs | 9-11 | August 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.
Basic reading:
Gill, G. 2006. Essential Mathematics for Political and Social Research Cambridge
Pollock III, Philip H. 2008. The Essentials of Political Analysis (3rd ed.). 2008. Washington, DC: Congressional Quarterly Press. King, Gary, Robert Keohane and Sidney Verba, 1994. Designing Social Inquiry: Scientific Inference in Qualitative Research, Princeton.
Field, A. 2005. Discovering Statistics Using SPSS London, Sage.
Hoover, K and Donovan, T. 2007. The Elements of Social Scientific Thinking (9th edition, Thomson Learning)