Module Information

Module Identifier
PGM2110
Module Title
Statistics for Experimental Scientists
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)
 

Course Delivery

Delivery Type Delivery length / details
Seminar 1 x 1 Hour Seminar
 

Assessment

Assessment Type Assessment length / details Proportion
Semester Assessment online assessments  60%
Semester Assessment Quantitative Research Report  40%
Supplementary Assessment retake failed elements of the module  100%

Learning Outcomes

On completion of this module, students should be able to:
1. Identify appropriate methods of analysis for different types of data.
2. Analyse data using a range of statistical analyses.
3. Interpret the results of data analyses.
4. Apply statistical knowledge in the content of postgraduate research.

Brief description

The module is comprised of a series of self-contained, e-learning based units delivered entirely through Blackboard but supported by optional workshops to provide help as required. A core of compulsory units will reinforce elements of basic statistics while a broader range of more advanced techniques will be available for students to select from according to study scheme and dissertation topic. The statistical techniques will be demonstrated using SPSS, a statistical package fully supported by the University.

Aims

An understanding of the principles of research design, the ability to statistically analyse data and the subsequent interpretation of such analyses are essential for Masters courses in Biological Sciences. This module builds on basic statistical principles that would have been covered at undergraduate level and develops procedures relevant to the specific MSc subject areas taught within IBERS, including: animal sciences, equine sciences, ecology.

Content

The module will consist of ten, self contained units each comprised of: Panopto video(s), describing and demonstrating a specific statistical procedure, written instructional material, relevant publications and articles, formative quizzes with feedback that can be attempted any number of times and a final summative quiz which is assessed, can only be attempted once and is time limited.

All students will undertake a core of six units reinforcing basic statistical procedures:

1. Data handling and presentation
2. T-tests
3. ANOVA
4. Post-hoc significance tests
5. Correlation/Regression
6. Non-parametric tests

Students will choose a further four units from a range of more advanced subject areas including the following:

• Multifactorial ANOVA
• Repeated measures/Split plot ANOVA
• Multivariate Analysis of Variance (MANOVA)
• Principal Component Analysis (PCA)
• Canonical Variate Analysis (CVA)
• Discriminant Function Analysis (DFA)
• Survey/questionnaire design and analysis

Module Skills

Skills Type Skills details
Application of Number Most aspects of the module will require manipulation of data and application of statistics.
Communication The ability to present results of scientific research and their statistical analysis in a clear and concise manner will be developed.
Improving own Learning and Performance Students need to be capable of organising themselves to ensure that sub-units are completed at an appropriate rate.
Information Technology Students will be expected to use statistical packages to manipulate and analyse data.
Personal Development and Career planning
Problem solving
Research skills Students will develop the skills required to interpret and evaluate data presented in the scientific literature.
Subject Specific Skills Students will be expected to identify, design and interpret the most appropriate statistical technique required in order to analyse the data generated from their own research
Team work

Notes

This module is at CQFW Level 7