Advanced Experimental Design and Analysis
| Code | School | Level | Credits | Semesters |
| LIFE4049 | Life Sciences | 4 | 10 | Autumn UK |
- Code
- LIFE4049
- School
- Life Sciences
- Level
- 4
- Credits
- 10
- Semesters
- Autumn UK
Summary
An advanced level biological experimental design and statistics course, building on basic undergraduate (Levels 1 and 2) training. Lectures discuss concepts in experimental design, biological probability, generalised linear modelling and multivariate statistics. Practical sessions build on this conceptual outline, giving hands on experience of problem solving and analytical software, and some basic programming skills.
Target Students
Students registered for the fourth year of the MSci degrees within the School of Life Sciences or on the Natural Sciences programmes, for the MSc course in Bioinformatics, for the MSc course in Molecular Genetics and Diagnostics. PGR students may attend but will not be assessed. Students who have not covered basic statistics, hypothesis-testing and experimental design earlier in their degree may find the module challenging. Biochemistry, Biochemistry and Genetics, and Molecular Genetics and Diagnostics students may find that the content is not centred on topics directly relevant to their projects.
Classes
This module may be delivered through lectures, seminars, workshops and labs etc.
Assessment
- 100% Coursework: 1500 word (or equivalent) problem-solving assignment.
Assessed by end of autumn semester
Educational Aims
Building on basic undergraduate training, this module will outline a range of statistical techniques that students are likely to encounter during their research projects. We will also discuss the most common experimental design problems faced by biologists. The objective is not to give detailed training in all techniques, but to provide a conceptual toolkit enabling students to develop solutions to a range of problems, and a basis from which to explore the relevant literature and software in their own time.Learning Outcomes
Students will:
- A2. Learn about current trends and developments in approaches to the design of experiments and the analysis of complex datasets in biology.
- A4. Learn to use appropriate terminology in statistics and experimental design when talking about their work.
- B1. Critically analyse and interpret published information and data.
- B3. Understand classical and complex problems in experimental designs and learn to recognise them in real biological scenarios.
- C1. Tackle research questions using quantitative analysis of data.
- C4. Undertake appropriate experimental design and statistical analysis.
- D4. Use and access information technology, including statistical packages and a programming language.
- D6. Manage and manipulate numerical data.