Unit name | Further Quantitative Methods |
---|---|
Unit code | SPOLM0016 |
Credit points | 20 |
Level of study | M/7 |
Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
Unit director | Dr. Eroglu-Hawksworth |
Open unit status | Not open |
Pre-requisites |
Participants should usually have already taken the unit ‘Introduction to Quantitative Research Methods in the Social Sciences’ (SPOLM0015), or be able to demonstrate equivalent expertise. |
Co-requisites |
None |
School/department | School for Policy Studies |
Faculty | Faculty of Social Sciences and Law |
Analysing Quantitative Data
This unit builds upon the new DTC module, Introduction to Quantitative Research Methods in the Social Sciences (SPOLM0015), by focusing upon techniques for the analysis of quantitative data. The unit covers three main topics:
Upon completion of this unit student should be able to:
The summative assessment tests all of the ILOs and accounts for 100% of the unit mark.
Lecture and demonstration. Many of the classes in this module involve an emphasis upon developing computer-based statistical analysis skills and will therefore be lab-based. These sessions will involve on-line classroom-based exercises designed to develop competency in using SPSS for the analysis of quantitative data.
The course comprises 3 days of teaching (1 day per week) made up of many sessions of 1-1.5 hours.
The summative assessment tests all of the ILOs and accounts for 100% of the unit mark.
Formative assessment will be primarily by means of student presentations delivered as part of the teaching program. Students will be asked to work in small groups to develop a research design in order to investigate a key social policy problem (e.g. ill health, crime, poverty) based upon exploration of a selected UK Data Archive teaching data set. Students will be asked to present their proposed research and will have an opportunity to receive feedback on this during the session.
Formative self-assessment by means of multiple choice questionnaires is also available to participants via the package “Statistics for the Terrified”. This will enable participants to better evaluate their progress, and to identify areas for revision or further development.
Many of the unit sessions are based upon lab-based activities involving analysis of large-scale datasets using the SPSS package. Students are asked to complete these tasks and write up their results in the associated workbooks which we review with students at the end of each session.
Summative assessment will be by means of a written assignment of not more than 4,000 words. Participants will be asked to apply the knowledge and skills they have developed during the course of the unit to the investigation of a key social policy problem based upon the secondary analysis of a large scale teaching data set.