1. Demonstrate professional level research planning skills appropriate to a professional Bioscientist.
Analysis, Enquiry, Problem Solving, Application

2. Demonstrate advanced skills in data handling, analysis and the use of standard statistical software
Learning, Analysis, Problem Solving, Application

3. Effectively communicate the salient features of experimental design and planning to a professional audience
Communication

4. Display knowledge of the techniques used by graduate analysts and understand their use in research investigations.
Analysis, Enquiry

1. Data Presentation and Analysis Portfolio (LO’s 2 and 4)
You will be asked to present and analyse data throughout the module. These tasks may include the use of descriptive statistics on provided data sets, understanding and using, confidence intervals and confidence levels, as well as the production of appropriate visual representations of data.

2. Project Grant Proposal (LO’s 1 and 4)
You will be asked to choose an area of your own interests and write a grant application for a research project following one of the major funding bodies grant criteria.

3 Grant Proposal Presentation (LO 3)
You will be asked to make an oral presentation of your Project grant proposal with a focus on the rationale and experimental design to an audience of your peers and tutors. Your presentation should include visual aids and occupy 15 minutes, plus an additional 5 minutes for questions. (FINAL ASSESSMENT).

This module is designed to allow you to critically engage with the literature in order to design experiments and studies that produce meaningful data at a level that would be of publishable quality. The module will provide you with the theoretical principles of experimental design, an understanding of new and evolving technologies that will support the research of the future, and the statistical framework within which to apply the fundamental concepts.

A main core of the module will be the acquisition of knowledge of the methods and techniques required to design, collect and analyse both quantitative and qualitative experimentally derived data. Additionally the module will also be dedicated to developing the essential management and leadership tools needed to implement and drive a successful experimental research project.

A range of topics will be covered and include areas such as scientific questioning, hypothesis framing, hypothesis testing, data management, questionnaire design, semi-structured interviews, methods of data reduction and exploration, regression analysis, multivariate techniques and advanced tests for difference. Techniques covered will include new and evolving technologies across a range of fields.

Exercises and tuition will help the explorations and testing of the data handling and statistical analysis capabilities of software such as Excel, SPSS or R.

This module is designed to allow you to critically engage with the literature in order to design experiments and studies that produce meaningful data at a level that would be of publishable quality. The module will provide you with the theoretical principles of experimental design, an understanding of new and evolving technologies that will support the research of the future, and the statistical framework within which to apply the fundamental concepts.

This module will contain tutor directed workshops, lectures and seminars designed to elucidate, explain and help understand the indicative content.

Computer-based statistical exercises will supplement the directly taught component. This will be designed to be studied independently and used to develop specific ideas introduced in the workshop sessions.

Directed independent problem-solving/tasks, to include distributed learning material, guided reading and completion of assessment tasks will occupy the remainder of the time

Dytham, C (2011), Choosing and Using Statistics: A biologist ¿s guide (3rd Edn), Wiley-Blackwell, Chichester, UK
Kabacoff, R I (2011), R in Action: Data analysis and graphics with R, Manning Publications Co, NY, USA
Pallant, J (2013), SPSS Survival manual: A step by step guide to data analysis using IMB SPSS (5th edn), McGraw-Hill Education, Berkshire, UK
Silverman, D (2015) Interpreting Qualitative Data 5th Edition. Sage Publications Ltd. NY
Wu, CFJ and Hamada, M. (2009) Experiments: Planning, Analysis, and Optimization. Wiley-Interscience, NY

Students are encouraged to focus on finding information on the techniques being investigated which may include technical manuals as well as primary literature and research reviews.

IT laboratories equipped with SPSS and R.