- Dr Jane Wellens (Head of Graduate School - University of Nottingham)
|Delivery Type||Delivery length / details|
|Seminar||1 x 1 Hour Seminar|
|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%|
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.
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.
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.
All students will undertake a core of six units reinforcing basic statistical procedures:
1. Data handling and presentation
4. Post-hoc significance tests
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
|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|
|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|
This module is at CQFW Level 7