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MA50259: Statistical design of investigations

[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 Mathematical Sciences
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 2
Further information on unit assessment Assessment Summary: CW 100%
Further information on unit assessment Assessment Detail:
  • Coursework 1 (CW 50%)
  • Coursework 2 (CW 50%)
Further information on supplementary assessment Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Further information on requisites Requisites: Before taking this module you must take XX50215
Description: Aims:
To understand the statistical aspects of the design of experimental and observational studies, and the associated methods of statistical analysis.

Learning Outcomes:

* Understand the principles of experimental design and observational studies
* Analyse data from experimental designs
* Employ sampling schemes with appropriate analyses.

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

Content:
Design of Experiments: principles of experimental design; planning of experiments; comparative experiments; and selected topics from common designs: completely randomised, randomised blocks, factorial experiments; fixed and random effects; associated analyses - analysis of variance. Observational studies v. experiments: problems of bias, confounding, difficulty of causal interpretation; planning observational studies; analysis: matching, adjusting for confounding variables; cohort studies; case-control studies.
Sampling target and sampled populations, finite populations, simple random sampling and selected topics from stratification and cluster sampling, ratio and regression estimators, randomised response methods.
Further information on programme availabilityProgramme availability:

MA50259 is Compulsory on the following programmes:

Department of Computer Science

Notes: