Module Information

Module Identifier
PGM0910
Module Title
Statistics in context: collecting, handling and presenting data
Academic Year
2018/2019
Co-ordinator
Semester
Semester 2 (Taught over 2 semesters)
Reading List
External Examiners
  • Dr Jane Wellens (Head of Graduate School - University of Nottingham)
 

Course Delivery

 

Assessment

Assessment Type Assessment length / details Proportion
Semester Assessment Presentation  40%
Semester Assessment 1000-1500 word report  60%
Supplementary Assessment Replacement written report  100%

Learning Outcomes

On successful completion of this module students should be able to:

1. Have developed an academic awareness of the issues and potential pitfalls around collecting data
2. Be able to define sample size, population and any covariates when conducting statistical analyses
3. Lead a discussion group on a data set of relevance to their studies
4. Be able to academically present statistical data effectively in order to make patterns clear.

Brief description

The course consists of a set of seminar 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. By looking at a variety of data sets through the course, student will develop an understanding of important questions to consider when deciding how to gather data and make statistical inference based on that data.

Aims

This module aims to provide students with a general framework which can be used to critique statistical data sets constructively. Students will develop a good understanding of the need for careful planning when preparing to collect statistical data. By looking at a range of data sets, and thinking carefully about what statistical questions the data can help to answer, students will develop their awareness of the implications of the often complex processes that accompany the collection and effective presentation of data sets.

Content

The content will depend on the range of disciplines represented. Through the semester, students will develop an understanding of the importance of considering the context in which data sets are generated, and appreciating the implications of the various decisions that accompany the gathering and presenting of statistical data. A template for well-structured data collection, handling and presentation is offered as a model on which to base any statistical investigation.

Module Skills

Skills Type Skills details
Application of Number The module will develop skills in extracting relevant information from quantitative data
Communication The module develops written and spoken communication skills via the coursework and presentation respectively. 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 course involves self-reflection and the critical evaluation one's own use of statistical data throughout. These skills are assessed both through the presentation and the written report after the delivery of the seminar.
Personal Development and Career planning Giving a presentation and participating in the group discussions will contribute to confidence in creative thinking and explaining scientific ideas.
Problem solving Through leading a discussion group on their own data, the students will need to identify the issues that arise in a consideration of the data in context
Research skills On completion of the module students should be able to use refined questioning to explore the patterns in statistical data sets. They will have used a clear schema for planning the collection, handling and presentation of data.
Subject Specific Skills Since the students will each lead a discussion group on their own data set, they will develop a deeper understanding of the issues surrounding their experiment or study.
Team work The facilitated group discussions encourage all participants to join in to generate collective insights about the data.

Notes

This module is at CQFW Level 7