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MA50289: Data science and statistics for health

[Page last updated: 09 August 2024]

Academic Year: 2024/25
Owning Department/School: Department of Mathematical Sciences
Credits: 12 [equivalent to 24 CATS credits]
Notional Study Hours: 240
Level: Masters UG & PG (FHEQ level 7)
Period:
Academic Year
Assessment Summary: CWRI 50%, EXCB 50%
Assessment Detail:
  • Case study (data analysis 1) (CWRI 25%)
  • Examination 1 (EXCB 25%)
  • Case study (data analysis 2) (CWRI 25%)
  • Examination 2 (EXCB 25%)
Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Requisites: While taking this module you must take XX50215 AND take MA50258 AND take MA50259 AND take MA50260
Learning Outcomes: After completion of the unit, students will be able to:
* describe the main data source types for studies in health and be able to critically evaluate their relative strengths and weaknesses,
* describe and implement the processes involved in initial data handing, preparation, and assessment,
* handle, manage and analyse health data in the context of legal, ethical, and professional considerations,
* select, apply, and interpret the results of appropriate standard statistical methods for analysing data from health studies
* deliver a critical and informative written report describing statistical analysis of health data


Aims: To learn about and give extensive experience of the concepts and methods of data science & statistics relevant to studies of health, including study sources, data management, statistical analysis, and interpretation and reporting.

Skills:
* Conceptual understanding of health study design and statistical analysis approaches (T,F,A)
* Critical interpretation of analytic output (T,F,A)
* Programming of data handling and statistical techniques (T,F,A)
* Technical report writing (T,F,A)

Content: In the first half, topics covered from: data sources in health: clinical trials, observational studies and routinely collected health databases; data management & checking for health data; data visualisation and communication of results to non-expert audiences; ethics and data protection for health studies; basic statistical analysis of data from health studies using a relevant software package (e.g. Python or R), such as t-tests, differences in proportions, randomisation tests, regression modelling to adjust for confounding.

In the second half, topics covered from: analysis of unstructured text data; causal diagrams, effect modification, mediation; statistical methods for survival data; meta-analysis; propensity scores for confounder adjustment; methods for handling missing data.

Course availability:

MA50289 is Compulsory on the following courses:

Department of Mathematical Sciences

Notes:

  • This unit catalogue is applicable for the 2024/25 academic year only. Students continuing their studies into 2025/26 and beyond should not assume that this unit will be available in future years in the format displayed here for 2024/25.
  • 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.