Last modified: 26 Feb 2018 19:47
Review of basics of probability theory, data exploration and analysis using the linear modelling framework; depending on the option taken - fundamentals of using geographic information systems (GIS); bioinformatics and their application; statistical computing with R; capturing data; experimental design.
|Session||First Sub Session||Credit Points||15 credits (7.5 ECTS credits)|
Using real biological cases studies, the first 3 weeks of the course will refresh and reinforce basic notions of statistics and statistical modelling. You will learn how to approach the analysis of biological data, introducing a workflow covering hypothesis formulation, graphical data exploration, statistical analysis, validation of assumptions and interpretation of results. This will take you to a level which will allow you to design, at least the first stages of your level 4 honours project
For the following 2 weeks of the course will allow you to choose from 4-6 options in advanced data handling techniques also pertinent to level 4 honours projects.
The course is intensive but alternates lectures followed by practical sessions so you can practice the taught principles with real data and benefit from considerable assistance from 3-4 staff and 5-6 demonstrators.
Students will attend 3 x 1hr lectures per week and 3 x 1hr practical session per week during the first 3 weeks. The following 2 weeks have a variable format depending on the choice of option. It is expected that students would spend a further 14-15 hours per week in self-study.
This course runs in weeks 7-11, and is scheduled in Thread 2, so may have contact hours in any or all of these times: Mondays, 14-18; Tuesday, all day; Friday, 14-18.
Information on contact teaching time is available from the course guide.
1st Attempt: First 3 weeks session: Continuous assessment by two tests (25% 5 each) and one final exam (25%).  Last 2 weeks session: Assessment based on test or practical report, depending on option selected.
Resit: As first attempt with opportunity to resit the failed component (s) and pass marks carried forward.
Tutorial/workshop sessions will provide opportunity for student-student and student-tutor interaction. Exercises completed during the practical sessions are supported by material that can be used for self-assessment and staff will provide informal verbal feedback during practical sessions.
Students will receive automated feedback on MCQ with opportunities to ask questions in online forum and Q&A sessions and written feedback on their practical reports.