- Academic Registry
Programme & Unit Catalogues

CM50341: Statistics for artificial intelligence

[Page last updated: 27 October 2020]

Follow this link for further information on academic years Academic Year: 2020/1
Further information on owning departmentsOwning Department/School: Department of Computer Science
Further information on credits Credits: 6      [equivalent to 12 CATS credits]
Further information on notional study hours Notional Study Hours: 120
Further information on unit levels Level: Masters UG & PG (FHEQ level 7)
Further information on teaching periods Period:
Semester 1
Further information on unit assessment Assessment Summary: CW 100%
Further information on unit assessment Assessment Detail:
  • Assessment detail for this unit will be available shortly. (CW 100%)
Further information on supplementary assessment Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Further information on requisites Requisites:
Description: Aims:
Students should gain an understanding of the basic theory of probability and statistics. Students will recognise when this theory can be applied in practice.

Learning Outcomes:
On completion of this unit, the student should be able to:
1. perform elementary mathematical operations in probability and statistics,
2. translate real-world problems into a probabilistic or statistical framework
3. solve statistical problems in abstract form,
4. critically interpret mathematical outcomes in a real-world context,
5. relate underlying theory to requirements in practical data science.

Problem solving (T, F, A),
Computing (T, F, A),
Written communication (F, A)

Example topics covered include: The laws of probability. Discrete andcontinuous random variables. Bayes' Theorem. Expectation, variance and correlation. Conditional and marginal distributions. Common distributions including the normal, binomial and Poisson. Statistical estimation including maximum likelihood. Hypothesis testing and confidence intervals.
Critical evalutation of mathematical computations and models on real world examples.
Further information on programme availabilityProgramme availability:

CM50341 is Optional on the following programmes:

Department of Computer Science
  • RSCM-AFM51 : Integrated PhD Accountable, Responsible and Transparent Artificial Intelligence


  • This unit catalogue is applicable for the 2020/21 academic year only. Students continuing their studies into 2021/22 and beyond should not assume that this unit will be available in future years in the format displayed here for 2020/21.
  • Programmes and units are subject to change in accordance with normal University procedures.
  • Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.
  • Find out more about these and other important University terms and conditions here.