Biomedical Engineering (MEng)
Probability and Statistics for Bioengineering
Module aims
To ensure that all students acquire a solid foundation in probability theory as well as the statistical knowledge and skills required for the advanced years of their Bioengineering programme.
Learning outcomes
Learning Outcomes - Knowledge and Understanding
- To describe data through statistical quantities such as mean and standard deviation
- To compute probabilities for random variables from probability distributions
- To explain the characteristics of the Gaussian and the Poisson distribution
- To explain the merit and the limitations of the central limit theorem
- To compute confidence intervals
- To test for statistical significance
- To perform linear regression and explain the results
Learning Outcomes - Intellectual Skills
- To compare different statistical quantities to describe data
- To compare and differentiate different probability distributions
- To judge different techniques for statistical tests
Learning Outcomes - Practical Skills
- To apply probabilistic descriptions to real-world data
- To apply statistical tests and regression to experimental data
- To be able to learn about further statistical methods and their applications
Learning Outcomes - Transferable Skills
- To recognize common statistical features in diverse data
- To employ analytical and numerical methods to mathematical problems
Module syllabus
Descriptive statistics and elements of probability
Discrete random variables and probability distributions
Continuous random variables and probability distributions
Joint probability distributions and random samples
Parameter estimation and intervals
Hypothesis testing
Regression
Pre-requisites
Mathematics I and II
Teaching methods
Labs: 60 hours
Assessments
Examinations:
● Written exam: ; 100% weighting
Rubrics: One summer exam, 60 minutes, worth 100% (for credit).
No type of previous exam answers or solutions will be available