## XX50215: Statistics for data science

[Page last updated: 23 October 2023]

Owning Department/School: Department of Computer Science
Credits: 6 [equivalent to 12 CATS credits]
Notional Study Hours: 120
Level: Masters UG & PG (FHEQ level 7)
Period:
Semester 1
Assessment Summary: EX 100%
Assessment Detail:
• Examination (EX 100%)
Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Requisites:
Learning Outcomes: After completion of the unit, students should be able to:
* perform elementary mathematical operations in probability and statistics,
* translate real-world problems into a probabilistic or statistical framework,
* solve statistical problems in abstract form,
* critically interpret outcomes in a real-world context,
* relate underlying theory to requirements in practical data science.

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.

Skills: Problem solving (T, F, A), computing (T, F, A), written communication (F, A)

Content: Topics covered will include: The laws of probability. Discrete and continuous 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.

Course availability:

#### XX50215 is Compulsory on the following courses:

Department of Computer Science

#### XX50215 is Optional on the following courses:

Department of Computer Science
• RSCM-AFM51 : Integrated PhD Accountable, Responsible and Transparent Artificial Intelligence
• RSCM-APM51 : Integrated PhD Accountable, Responsible and Transparent Artificial Intelligence
• USCM-AFM01 : MComp(Hons) Computer Science (Year 4)
• USCM-AAM02 : MComp(Hons) Computer Science with Study year abroad (Year 5)
• USCM-AKM02 : MComp(Hons) Computer Science with Year long work placement (Year 5)
• USCM-AFM27 : MComp(Hons) Computer Science and Artificial Intelligence (Year 4)
• USCM-AFM14 : MComp(Hons) Computer Science and Mathematics (Year 4)
• USCM-AAM14 : MComp(Hons) Computer Science and Mathematics with Study year abroad (Year 5)
• USCM-AKM14 : MComp(Hons) Computer Science and Mathematics with Year long work placement (Year 5)
Department of Mathematical Sciences
• TSMA-AFM19 : MSc Mathematics with Data Science for Industry
• TSMA-AWM19 : MSc Mathematics with Data Science for Industry

 Notes: This unit catalogue is applicable for the 2023/24 academic year only. Students continuing their studies into 2024/25 and beyond should not assume that this unit will be available in future years in the format displayed here for 2023/24. Courses 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.