Last modified: 31 Jul 2023 11:19
This course will introduce you to the key principles of ethical research in bioengineering, and cover core topics such as experiment design, basic statistical analysis, and how to review the scientific literature.
| Study Type | Postgraduate | Level | 5 |
|---|---|---|---|
| Term | Second Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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This is a broad course covering essential topics for the conduct of research in bioengineering. As well as an understanding of the principles of ethical and reproducible research, you will develop skills in coding and the analysis of data, a knowledge of experiment design and appropriate statistical analysis. Indicative topics will include:
- How to read a paper, with journal club sessions
- Reviewing the literature and identification of a research question
- Experiment design and hypothesis testing
- Ethical conduct of research with human participants, including clinical trials of medical devices.
- Introduction to programming for data analysis
- Data processing and statistical methods
Information on contact teaching time is available from the course guide.
Coursework report - statistical analysis (30%)
Research project proposal (70%)
Resit
Resit failed component(s)
There are no assessments for this course.
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Understand | Demonstrate understanding of the ethical conduct of research involving human participants, their tissues or their data. |
| Procedural | Evaluate | Critically evaluate the research design and methodologies used in scientific literature in the field of biomedical engineering. |
| Procedural | Evaluate | Compare the effectiveness of clinical trial designs in biomedical engineering, such as double-blind, randomised, matched and retrospective designs. |
| Procedural | Apply | Perform common statistical tests, using software packages, such as confidence intervals and comparisons of means (e.g. t-test and ANOVA) and evaluate their outcomes. |
| Procedural | Create | Communicate findings for non-specialist audiences using simple concepts such as probability or odds. |
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