Module Information
Course Delivery
| Delivery Type | Delivery length / details |
|---|---|
| Seminar | 11 x 1 Hour Seminars |
| Workshop | 1 x 2 Hour Workshop |
Assessment
| Assessment Type | Assessment length / details | Proportion |
|---|---|---|
| Semester Assessment | Presentation | 40% |
| Semester Assessment | 1000-1500 word report | 60% |
| Supplementary Assessment | Resit presentation | 40% |
| Supplementary Assessment | Resit 1000-1500 word report | 60% |
Learning Outcomes
On successful completion of this module students should be able to:
Demonstrate an awareness of the issues and potential pitfalls around collecting data
Understand the importance of clearly defining the sample, the population of interest and any covariates when conducting statistical analyses
Lead a discussion group on a data set of relevance to their studies
Understand the principles behind experimental design
Demonstrate understanding of how to present statistical data effectively in order to make patterns clear
Brief description
This module was designed to be an integral component of the RT courses which the University has introduced in order to meet the joint funding Research councils statement on Research Training. Through this module Masters and PhD students will gain a broad knowledge of a range of transferable skills which they can apply in a variety of research contexts.
Aims
The module is aimed at postgraduates from any discipline where they are handling quantitative data as part of their research
Content
The second semester consists of discussions about different data sets. Some data sets will be presented by the staff members running the course. Others will be presented by postgraduate students on the course. The content will very much depend on the range of disciplines represented on the course
Module Skills
| Skills Type | Skills details |
|---|---|
| Application of Number | The module will develop skills in the analysis of small and large scale data sets using quantitative techniques. |
| Communication | The module develops written communications skills via the coursework. Students will be expected to submit their work in word-processed format and the presentation of work should reflect effective expression of ideas and good use of language skills in order to ensure clarity and coherence. |
| Improving own Learning and Performance | The module will enhance the student’s awareness of conducting research in a manner which is consistent with professional practice. Students will improve their own learning and performance by undertaking directed but independent study and research, and deciding upon the direction taken for their essay submissions. Time management will be crucial in preparation for the assessments. |
| Information Technology | The module will develop skills in managing research data, including the use of IT in such data management. There will also be development of skills in the use of software for quantitative techniques. Students will be encouraged to use electronic sources of information and will be expected to submit their work in wor-processed format. |
| Personal Development and Career planning | The module offers students a range of skills which will be applicable during doctoral research and subsequent careers |
| Problem solving | Independent project work and problem solving are integral to the module’s aims. Coursework will require development of problem solving skills and independent research skills. |
| Research skills | On completion of the module, students should be able to: -collect quantitative data -demonstrate awareness of the relevant methodologies for data acquisition |
| Subject Specific Skills | The module will develop students’ skills in the application of advanced quantitative methods including time series analysis, forecasting, event studies and performance measurement |
| Team work | Practicals and workshops will involve discussions where students are obliged to address the core issues as a group. |
Notes
This module is at CQFW Level 7