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DRPS : Course Catalogue : Deanery of Biomedical Sciences : Biomedical Sciences

Undergraduate Course: Biomedical Sciences 3: Obtaining, Analysing and Evaluating Data (VS1) (BIME09009)

Course Outline
SchoolDeanery of Biomedical Sciences CollegeCollege of Medicine and Veterinary Medicine
Credit level (Normal year taken)SCQF Level 9 (Year 3 Undergraduate) AvailabilityPart-year visiting students only
SCQF Credits20 ECTS Credits10
SummaryThis 20 credit single semester course for visiting students comprises the first semester of a two semester 40 credit Biomedical Sciences 3 (BMS3) course that is compulsory for all third year Biomedical Sciences students. A second year course, Biomedical Sciences 2 (BMS2), is an essential prerequisite for Biomedical Sciences students. Visiting students should be aware that a significant component of 'BMS3: Obtaining, Analysing, and Evaluating Data (VS1)' involves statistical data analysis using 'R' programming language building on material from BMS2. Visiting students who have not previously taken courses covering equivalent material, specifically statistical analysis, to BMS2 may struggle with 'BMS3: Obtaining, analysing, and Evaluating Data (VS1)' and should consider this before enrolling as a visiting student.

The course aims to provide students with a secure grounding in the core skills of understanding scientifically valid experiments, collecting, analysing and interpreting data, communicating results, and in being able to critically evaluate primary research papers.

Teaching will be through a combination of lectures, a practical (wet lab), workshops (dry lab), and tutorials. A variety of in-course assessments will give an opportunity to students to assess their understanding of material and to receive both formative and summative feedback.
Course description In broad terms, this course focuses on how researchers obtain, analyse and evaluate data in the Biomedical Sciences.


Understanding and evaluating research papers: Two lectures in Semester 1 focusing on the research literature, peer review, and how to quickly assimilate key points of a paper, plus evaluation of papers. These topics are also reinforced in tutorials.
Data Analysis: Six lectures in Semester 1, some with associated practice sessions following the lecture, on data handling, statistical analysis (use and misuse), and formal hypothesis testing.

Practicals and Workshops

Practical 1 (Wet Laboratory): Genes and Transgenic mice: Studying gene function using a transgenic mouse model. Hypothesis testing, quantitative analysis, and data presentation and interpretation linked to an ICA practical report.
Workshop 1 (Dry Laboratory): Analysing data with R.
Workshop 2 (Dry Laboratory): Additional data analysis skills.


Two tutorials will focus on training in generic paper analysis skills. The papers used will be common to the whole class. Assessment of this learning outcome will then be tested in a December exam, based on a paper that will be provided to the class several weeks beforehand. Questions will address issues of experimental design, choice of techniques, hypotheses, data analysis and interpretation.

Assessment of the learning outcomes will be tested in ICA and the December exam.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Academic year 2022/23, Part-year visiting students only (VV1) Quota:  None
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 17, Seminar/Tutorial Hours 3, Supervised Practical/Workshop/Studio Hours 11, Online Activities 2, Feedback/Feedforward Hours 1, Summative Assessment Hours 2, Revision Session Hours 1, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 159 )
Assessment (Further Info) Written Exam 50 %, Coursework 50 %, Practical Exam 0 %
Additional Information (Assessment) ICA:Exams 50:50 weighting
December Exam: 50% of course

ICA elements:
Data Analysis ICA: 20% of course
Report on Practical 1 (genes and transgenic mice): 30% of course
Feedback Feedback on the in-course assessments will be provided, and a feedback session for the December exam will be held.
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S1 (December)1:30
Learning Outcomes
On completion of this course, the student will be able to:
  1. * developed an understanding of broad themes within contemporary biomedical sciences as well as an understanding of key experimental approaches, plus an appreciation of when they can be used, their strengths and weaknesses, and the type of data they produce
  2. * acquired the ability to efficiently search for, understand, interpret, and evaluate primary biomedical research papers ('paper analysis') as well as the ability to frame scientific hypotheses and to design scientifically valid experiments to test them using appropriate experimental techniques
  3. * gained experience in collecting sets of data, analysing them, and testing formal hypotheses using statistical software programs
  4. * demonstrated technical skill in writing up concise and accurate practical reports as well as shown understanding of the theory relating to the practicals
  5. * gained competence in the accurate and effective communication of biomedical concepts and data as well as gained experience of working as a team member
Reading List
It is not easy to recommend books for this course as there is a diverse background in knowledge and previous courses taken. It is not necessary to buy any books at all.

If your basic mathematics is a bit rusty, you should first read the "Quantitative Skills Refresher Notes" posted on Learn.

The following may be useful for those who find maths and statistics a challenge:
Maths & Stats for the life and medical sciences, M. Harris et al., 2005, Scion Publishing Ltd. This is part of the "CatchUp" series.

Intuitive Biostatistics, H. Motulsky (2nd Edn) 2010, OUP.

A good book covering experimental design, statistical analysis, and much else besides is:
Asking Questions in Biology, C. Barnard, F.Gilbert, P.McGregor, (4th edn) 2011, Pearson.
(The 3rd edition, published in 2007, would also be fine.)

Check that the books are appropriate for your knowledge background by consulting a library copy before purchase. Note that you don¿t always need the most recent edition for statistics/maths books ¿ things have not moved on that much at this level. Second hand books will do.

A fairly comprehensive set of papers on statistics by Bland et al. can be found at:
Note that after following the link to a particular paper it is best to select the PDF version rather than viewing the default HTML version.

Also, the British Medical Journal has produced an excellent collection of material regarding experimental design and statistics:

Other papers will also be listed by individual lecturers.
Additional Information
Graduate Attributes and Skills Not entered
Course organiserDr Thomas Pratt
Tel: (0131 6)51 1707
Course secretaryMr Stewart Smith
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