XX50215: Statistics for data science
[Page last updated: 23 October 2023]
Academic Year:  2023/24 
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:  
Supplementary Assessment: 
 Likeforlike 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 realworld problems into a probabilistic or statistical framework,
* solve statistical problems in abstract form,
* critically interpret outcomes in a realworld 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
 TSCMAFM51 : MRes Accountable, Responsible and Transparent Artificial Intelligence
 TSCMAFM52 : MSc Accountable, Responsible and Transparent Artificial Intelligence
 TSCMAFM45 : MSc Data Science
 TSCMAWM45 : MSc Data Science
 TSXXAFM06 : MSc Data Science and Statistics
 TSXXAWM06 : MSc Data Science and Statistics
 TSCMAFM48 : MSc Machine Learning and Autonomous Systems
 TSCMAWM48 : MSc Machine Learning and Autonomous Systems
XX50215 is Optional on the following courses:
Department of Computer Science
 RSCMAFM51 : Integrated PhD Accountable, Responsible and Transparent Artificial Intelligence
 RSCMAPM51 : Integrated PhD Accountable, Responsible and Transparent Artificial Intelligence
 USCMAFM01 : MComp(Hons) Computer Science (Year 4)
 USCMAAM02 : MComp(Hons) Computer Science with Study year abroad (Year 5)
 USCMAKM02 : MComp(Hons) Computer Science with Year long work placement (Year 5)
 USCMAFM27 : MComp(Hons) Computer Science and Artificial Intelligence (Year 4)
 USCMAFM14 : MComp(Hons) Computer Science and Mathematics (Year 4)
 USCMAAM14 : MComp(Hons) Computer Science and Mathematics with Study year abroad (Year 5)
 USCMAKM14 : MComp(Hons) Computer Science and Mathematics with Year long work placement (Year 5)
Department of Mathematical Sciences
 TSMAAFM19 : MSc Mathematics with Data Science for Industry
 TSMAAWM19 : 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 prerequisite rules.
 Find out more about these and other important University terms and conditions here.
