Module Information

Module Identifier
PGM0910
Module Title
Statistics in context: collecting, handling and presenting data
Academic Year
2016/2017
Co-ordinator
Semester
Semester 2 (Taught over 2 semesters)
External Examiners
  • Dr Jane Wellens (Head of Graduate School - University of Nottingham)
 
Other Staff

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 first semester sessions include design of experiments including factorial designs, analysis of variance and considerations of the power of statistical tests
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