Course overview
The aim of this course is to introduce probability theory, random variables, and basic stochastic processes. Probability is the branch of mathematics that deals with modelling uncertainty with important applications in all areas of science, engineering, economics, and everyday life. It also forms the fundamental basis for many other areas in the mathematical sciences including statistics, optimisation, stochastic processes, risk modelling, decision making, machine learning and AI.
- Random Variables
- Joint Distributions
Course learning outcomes
- Translate real-world problems from verbal descriptions into probability models
- Explain the common named discrete and continuous random distributions and apply them to modelling situations
- Apply the formal rules of probability, conditional probability and independence to calculate probabilities and expectations
- Demonstrate understanding of probablistic limit laws and apply them to relevant situations
- Understand how joint distributions encode the behaviour of multiple random variables and exploit this for modelling and analysis of problems
Degree list
The following degrees include this course