TMA4265 Stochastic Processes, Autumn 2014

The curriculum consists of

• Chapter 1: Introduction to probability theory assumed to be known
• Chapter 2: Random variables assumed to be known
• Chapter 3: Conditional probability and condititional expectation, 3.1 - 3.5, 3.6.3
• Chapter 4: Markov chains, 4.1 - 4.9
• Chapter 5: The Exponential Distribution and the Poisson Process, 5.1 - 5.3
• Chapter 6: Continuous-time Markov chains, 6.1 - 6.6
• Chapter 8: Queueing theory, 8.1 - 8.3, 8.5, 8.9.1, 8.9.2
• Chapter 10: Brownian motion, 10.1 - 10.3

in Ross, S. (2014). Introduction to Probability Models, 11th edn, Academic Press". Everything covered in the lectures, project and exercises is also part of the curriculum.