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XX50215: Statistics for data science

[Page last updated: 15 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 50%, EX 50%
Further information on unit assessment Assessment Detail:
  • Coursework (CW 50%)
  • Examination (EX 50%)
Further information on supplementary assessment Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Further information on requisites Requisites: While taking this module you must take CM50264
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:
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.

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.
Further information on programme availabilityProgramme availability:

XX50215 is Compulsory on the following programmes:

Department of Computer Science

XX50215 is Optional on the following programmes:

Department of Computer Science
  • RSCM-AFM51 : 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-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)

Notes: