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Semester 1

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

Subject

Biomedical Sciences

College

MVM

Credits

20

Normal Year Taken

3

Delivery Session Year

2023/2024

Pre-requisites

Course Summary

This 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.LecturesUnderstanding 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 WorkshopsPractical 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.TutorialsTwo 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.

Assessment Information

Written Exam 50%, Coursework 50%, Practical Exam 0%

Additional Assessment Information

ICA:Exams 50:50 weightingExams:December Exam: 50% of course ICA elements:Data Analysis ICA: 20% of courseReport on Practical 1 (genes and transgenic mice): 30% of course

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