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

Intended Learning Outcomes (ILOs)
This module's assessment will evaluate your achievement of the ILOs listed here - you will see reference to these ILO numbers in the details of the assessment for this module.
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.

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:

Topic 1: Introduction: why use quantitative data and

Topic 2: Inferential statistics, a primer

Topic 3: Collecting data, sampling, data management and data integrity

Topic 4: Describing data and dealing with missing data

Topic 5: Writing up the results

Topic 6: Testing relationships between variables

Topic 7: Visual displays of data

Topic 8: Multivariate statistics

Topic 9: Ordinal and binomial data Topic 10: Advanced techniques Topic 11: Student Presentations

The module will be taught through 7 weekly two-hour sessions (including introductory session). There will be a mix of formal lecture 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
14	136	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	14 hours	7 weekly two-hour sessions (including introductory session).
Guided independent study	66	Reading, thinking and preparing for weekly sessions
Guided independent study	10	Web-based learning
Web-based learning	60	Preparation and completion of assessments

Online Resources

This module has online resources available via ELE (the Exeter Learning Environment).