Quantitative Skills for Biomedical Sciences

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• To develop skills in statistical analysis using Graphpad Prism.
• Apply power analysis for animal based research and appreciate its use in the 3Rs.
• Development of linked biochemical assays - Beer's law calculations; Standard curve;Data fitting;;
• Appreciate how clinical trials are conducted and the use of a double-blind random controlled trials.
• Appreciate the benefits and drawbacks of model systems for biomedical research.
• Understand the distinction between different data types
• To appreciate what is meant by statistical significance.
• Appreciate the importance of sample size, and the problems associated with underpowered and overpowered studies.
• Use the Henderson–Hasselbalch equation to make buffers
• Develop skills to use the statistical package Graphpad Prism to analyse and present data.
• Ordering data –The use of heat maps and dendrograms to present data

Students would be expected to gain appreciation of how to test a scientific question. Students also will gain an understanding of the need for mathematics in laboratory settings

The use of controlled experiments will be explored, and how it applies to both laboratory, animal and human based (clinical trials) studies. Students will understand how experiments are powered so as to get the right number of animals/subjects, and the importance of this in terms of conducting experiments, and the failings associated with getting this correct.

Students will gain an understanding of why model systems are used and given examples of their usefulness and their drawbacks- for example the use of inbred strains of mice.

Formative

This is how we’ll give you feedback as you are learning. It is not a formal test or exam.

Blackboard-based self-assessment exercises and quizzes

• Assessment Type: Formative
• Feedback:
• Final Assessment: No
• Group Work: No

Summative

This is how we’ll formally assess what you have learned in this module.