Introductory description

This module follows Probability 1 developing the theory of probability distributions, conditional expectation, modelling and other fundamental concepts. This module aims to develop students’ ability to create probabilistic arguments and models.

This module is core for students with their home department in Statistics and is not available to students from other departments. Students from other departments should consider ST120 Introduction to Probability.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

This module covers the following: common families of probability distributions, conditional expectation, probabilistic modelling, moment generating functions and the central limit theorem

Learning outcomes

By the end of the module, students should be able to:

• interpret key ideas of probability and calculate associated probabilities and expectations of random variables
• interpret concepts relating to the theory of probability distributions
• describe the role of randomness in mathematical modelling of real world situations

Indicative reading list

Ross, S. (2014). A first course in probability. Pearson;
Pitman, J. (1999). Probability, Springer texts in Statistics;
Suhov and Kelbert, Probability and Statistics by Example: Basic Probability and Statistics.

View reading list on Talis Aspire

Subject specific skills

• Demonstrate facility with advanced mathematical and probabilistic methods.

• Select and apply appropriate mathematical and/or statistical techniques.

• Demonstrate knowledge of key mathematical and statistical concepts, both explicitly and by applying them to the solution of mathematical problems.

• Create structured and coherent arguments communicating them in written form. 

• Construct and develop logical mathematical arguments with clear identification of assumptions and conclusions.

• Reason critically, carefully, and logically and derive (prove) mathematical results.

Transferable skills

• Problem solving: Use rational and logical reasoning to deduce appropriate and well-reasoned conclusions. Retain an open mind, optimistic of finding solutions, thinking laterally and creatively to look beyond the obvious. Know how to learn from failure.
• Self awareness: Reflect on learning, seeking feedback on and evaluating personal practices, strengths and opportunities for personal growth.
• Communication: Written: Present arguments, knowledge and ideas, in a range of formats.
• Professionalism: Prepared to operate autonomously. Aware of how to be efficient and resilient. Manage priorities and time. Self-motivated, setting and achieving goals, prioritising tasks.