ADULT CARDIORESPIRATORY CARE|CARDIAC AND PULMONARY REHABILITATION

Summary

This module explores the role of the advanced cardiorespiratory physiotherapist, integrating skills and techniques, theoretical concepts, clinical...

This module represents the year spend abroad by students following the MSci Statistical Science (International Programme). Whilst on the year abroad, students...

International Programme: Year Abroad (STAT0016)

This module represents the year spend abroad by students following the MSci Statistical Science (International Programme). Whilst on the year abroad, students will take courses at the host institution relevant to their field of study. Students should discuss these course choices with the Study Abroad Tutor, who must approve them. Course delivery methods and assessment will be determined by the host institution. The marks awarded by the host institution will then be converted to a single UCL equivalent mark and entered as the result for this module, for the purpose of degree classification.

Aims - This module aims to provide an introduction to the study of systems which change state stochastically with time and to facilitate the development of...

Introduction to Applied Probability (STAT0007)

Aims - This module aims to provide an introduction to the study of systems which change state stochastically with time and to facilitate the development of skills in the application of probabilistic ideas. It is primarily intended for second and third year students registered on the undergraduate degree programmes offered by the Department of Statistical Science, or jointly with other departments. It also serves as an optional module for students taking the mathematics and statistics stream of the Natural Sciences degree (with prerequisite: STAT0005).

Objectives - On successful completion of the module a student should understand the Markov property in discrete and continuous time; for discrete-time Markov chains, be able to find and classify the irreducible classes of intercommunicating states, calculate absorption or first passage times and probabilities, assess the equilibrium behaviour; for simple examples of continuous-time Markov chains, be able to write down the forward equations, find and interpret the equilibrium distribution.

Applications - Stochastic processes are vital to applications in finance and insurance, and have many applications in biology and medicine, and in the social sciences. They also play a fundamental role in areas such as queueing theory and the study of system reliability. The material in this module can be applied to simplified real-world situations, and provides the foundations for further study of more complex systems.

Content - Revision of conditional probability. Markov Chains (discrete time and states): transient and equilibrium behaviour, first passage times, classification of states, applications. Markov processes (continuous time, discrete states): general theory, forward and backward equations, equilibrium distributions; Poisson process, interval and counting properties; birth and death processes and other simple examples.

Key texts - Available from ReadingLists@UCL.