- Dr Helen West (Associate Professor in Environmental Biology, Faculty of Science, University of Nottingham - University of Nottingham)
- Dr Debbie Nash
- Dr Gordon Allison
- Professor Karl Hoffmann
- Dr Marco Arkesteijn
- Dr Martin Swain
- Dr Peter Dennis
- Mr David Powell
- Dr Dylan Phillips
- Professor Luis Mur
- Dr Sebastian Mcbride
- Dr Matthew Hegarty
- Mr Manod Williams
- Dr Ruth Wonfor
- Dr Sarah Dalesman
- Dr Joe Ironside
- Dr Rhys Jones
- Dr Russ Morphew
- Dr Ana Winters
- Ms Mary Jacob
- Dr Alison Watson
- Dr Gemma Beatty
- Professor John Doonan
- Dr John Scullion
- Dr Mina Davies-Morel
- Dr Arwyn Edwards
- Dr Claire Risley
- Dr Christina Marley
- Dr Gareth Griffith
- Professor Huw Jones
- Dr Jessica Adams
- Dr Justin Pachebat
- Dr Natasha De Vere
- Professor Peter Brophy
|Delivery Type||Delivery length / details|
|Miscellaneous||1 x 1 Hour Miscellaneous|
|Workshop||2 x 3 Hour Workshops|
|Lecture||18 x 1 Hour Lectures|
|Workshop||17 x 1 Hour Workshops|
|Assessment Type||Assessment length / details||Proportion|
|Semester Assessment||11 x summative on line assessments, related to 13 online tutorial steps about data handling and statistics.||50%|
|Semester Assessment||Scientific writing assignment related to research project topic (2500 words - all content)||25%|
|Semester Assessment||Critical review of advanced technique in the biosciences (2500 words - all content)||25%|
|Supplementary Assessment||Students must take elements of assessment that are equivalent to those that led to failure of the module||100%|
On successful completion of this module students should be able to:
1. Apply statistical knowledge in the context of postgraduate research using appropriate methods for different types of data.
2. Analyze and interpret the results from a range of different statistical analyses.
3. Assess the potential of genomic, biomechanical and spacial analytical approaches to biological/environmental investigations.
4. Generate appropriate research hypotheses and research objectives.
5. Assimilate and synthesizing of information from a variety of sources.
6. Clearly communicating research findings.
- Experimental design, data handling and statistical analysis, and
- An awareness of advances in technology and of how of cutting-edge analytical techniques have transformed bioscience research. This will provide support to the students in designing research projects and in analysing data. Guidance via tutorials and assignments will practice and hone scientific writing skills.
Formative and summative tests built around online resources already available within the Institute will cover quantitative and qualitative statistical methods for analyzing data.
Initial 'steps' will revisit basic statistical theory and analytical tests namely:
• t-tests, ANOVA, post-hoc significance tests, data handling and presentation, correlation/regression and non-parametric tests.
The online tutorial steps will then progress onto advanced considerations in experimental design and a range of more advanced statistical procedures including:
• Multifactorial ANOVA, repeated measures, split plot ANOVA, Multivariate Analysis of Variance (MANOVA), principal component analysis, canonical variate analysis (CVA), discriminant function analysis (DFA), survey/questionnaire design and analysis.
Section Two: Research Proposal or Funding Application
The theory, principles and practices of the scientific research method will be taught to evaluate existing research published in a range of different sources and to prepare students for independent research. MSc students complete a research proposal (linked with BRM3560) Integrated Masters and MRes students will prepare a grant application. Exercises will be related to student’s dissertation topics.
Section Three: Analytical Techniques and Communication of Scientific Information in the Biosciences
These learning activities, presented by research-active staff in a laboratory or seminar setting, will introduce students to a number of developments in the biosciences in order to help students to understand advances in methods and analytical techniques that have transformed bioscience research. Students will be introduced to a variety of research methods relevant to their PGT scheme subject and will select one of the advances for detailed critical review.
|Skills Type||Skills details|
|Application of Number||Students will be taught statistical techniques and expected to complete both formative and summative assessment.|
|Communication||Students will be expected to be able to express themselves appropriately in their assignments.|
|Improving own Learning and Performance||Detailed feedback will be given for assignment work. Workshops will serve to scaffold online learning of data analysis and statistics.|
|Information Technology||Students will be required to source information from a variety of scientific publication databases and be taught to use specialist statistical software.|
|Personal Development and Career planning||Research Project Plan or Grant Application - developed in collaboration with supervisor.|
|Problem solving||Online quizzes will be used to help develop and improve students' problem solving skills.|
|Research skills||Students will be required to undergo directed self-study and so will develop their literature research and information synthesis skills.|
|Subject Specific Skills||Advanced statistical methods, genomic, spatial analytical and biochemical applications or other techniques relevant to degree scheme.|
This module is at CQFW Level 7