MA3210 - Probability and Stochastic Processes

This subject will provide students with fundamental concepts of probability theory, random variables, and notions of random processes with applications. The theoretical foundations will be studied alongside with laboratory practice using a computer language such as MATLAB and/or R. Topics include: Elementary Probability: Counting and Probability Rules; Random Variables and Probability Distributions: Continuous and Discrete Cases; Multiple Random Variables and Functions of Random Variables; Statistical Properties of Random Variables: Expectation and Moments; Important Discrete and Continuous Distributions; Sequences of Random Variables and Random Vectors; Random Processes: Characterisation, Properties and Special Processes; Stochastic Systems, Noise and Spectrum Estimation; Applications (e.g. filtering, signal processing, dynamic systems identification)

Learning Outcomes

• describe and explain fundamentals of probability theory, random variables, and random processes, both in continuous as well as in discrete spaces;
• apply the fundamentals of probability theory and random processes to mathematically model practical problems involving uncertainty;
• apply the fundamentals of probability theory and random processes to determine theoretical solutions to the created models;
• perform simulations of the real problems and the corresponding mathematical models and solutions using a computer language such as MATLAB or R.

Subject Assessment

• end of semester exam (60%)
• assignments (40%).

Note: Minor variations might occur due to the continuous Subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.