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Last modified: 22 May 2019 17:07

Course Overview

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.

Course Details

Study Type Undergraduate Level 3
Session First Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus None. Sustained Study No
  • Professor Michelle Pinard

What courses & programmes must have been taken before this course?

  • Either Programme Level 3 or Programme Level 4
  • Any Undergraduate Programme (Studied)
  • One of BSc Biology (Studied) or BSc Conservation Biology (Studied) or BSc Zoology (Studied) or BSc Animal Ecology (Studied) or BSc Marine Biology (Studied) or BSc Animal Behaviour (Studied) or BSc Behavioural Biology (Studied) or MSci Biological Sciences (Studied) or BSc Biological Sciences (Honours) (Studied) or BSc Plant and Soil Sciences (Studied) or Bachelor Of Science In Environmental And Forest Management (Studied) or BSc Ecology (Studied) or BSc Forestry (Studied) or BSc Forest Sciences (Studied) or BSc Environmental Science (Studied)

What other courses must be taken with this course?


What courses cannot be taken with this course?

  • BI3007 Experimental Design, Analysis and Presentation (Studied)

Are there a limited number of places available?


Course Description

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.

Associated Costs


Further Information & Notes

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.   


Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers

Summative Assessments

1st Attempt: Three Class Tests (25% each), Report or online test, depending on which option student selects (25%)


Resit: As first attempt with opportunity to resit the failed component (s) and pass marks carried forward.

Formative Assessment




Class Test: the test is implemented through MyAberdeen as an online assessment, feedback is embedded for both correct and incorrect answers; the feedback is released to students two days after the deadline.

Reports receive individual written feedback

Course Learning Outcomes


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