This course introduces students to fundamental concepts in univariate probability theory.

Lectures: Course taught in the first two thirds of the semester (Monday to Thursday at 9.00 am with fewer lectures later on)
Workshops and drop-in help rooms arranged via MyCampus (several groups available).

End-of-course examination (80%); coursework (20%).

Reassessment will, generally, not be available for the coursework.

Reassessments are normally available for all courses, except those which contribute to the Honours classification. For non Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below. 

Reassessment will, generally, not be available for the coursework component of this course.

The aims of this course are:

■ to introduce students to fundamental concepts in probability theory;

■ to introduce students to the importance of stating and deriving results formally;

■ to equip students to apply probability to solve problems from a wide range of disciplines;

■ to promote an interest in Probability and Statistics and hence encourage students to study more advanced courses.

By the end of this course students will be able to:

■ state the Axioms of Probability;

■ state, use and rigorously prove basic propositions of probability theory;

■ explain the terms probability distribution and random variable;

■ write down general definitions of moments (including the expected value and variance) as well as the moment-generating function, derive general properties from these definitions, and compute moments in particular cases;

■ find the distribution of transformed random variables;

■ recognise basic discrete and continuous probability distributions in a context, and use them to obtain probabilities and moments;

■ apply probability results to solve a wide range of practical problems.

Minimum requirement as in code of assessment