MSc Health Data Science

This module will provide the opportunity for students to aid their development as a Health Data Scientist by exploring the literature on advanced statistical topics.  The topics covered are highly relevant for advanced understanding and practice of health research and Health Data Science, for example, Machine learning in clinical prediction models, Meta-analysis and evidence synthesis, and Analysis of longitudinal data.  The module is delivered by academics who are active researchers in the areas that they are teaching on and students will be encouraged to access, read, appraise and discuss recently published research.  Running through all the topics will be the principles of good study design and sound statistical thinking.

The unit aims to:

• Consolidate and build on the fundamental statistical content in Semester 1 modules
• Explore advanced statistical topics
• Foster statistical thinking
• Enable students to engage with and critically appraise published research
• Promote reasoned discussion and respectful debate
• Develop group working and presentation skills

This module promotes learning through engagement with the research literature on advanced statistical topics.  The twice-weekly face-to-face sessions will be used to introduce substantive topics, highlight specific areas of the literature and explore the background to important research questions.  However, the key focus of these face-to-face sessions will be to facilitate discussion and debate on current statistical research questions, as well as to scaffold literature-based individual or group tasks and, subsequently, to allow students to deliver their findings, for example via group presentations.  The aim is for students to feel equipped to actively participate in ongoing statistical debates and to be able to understand and probe different views in current areas of methodological controversy.  To encourage participation from all students, and in particular to allow non-verbal participation in discussions, electronic tools such as Google Jamboard will be available.  

Wherever possible, sessions will be captured and made available to watch online.  Online tutor support will be available via blackboard and email.  Office hours with course leaders (face-to-face and/or online) will also help ensure the availability of academic staff for student support.
 

• Describe and identify common statistical issues in health research
• Explain key methodological ideas related to the substantive statistical topics covered

• Apply methodological understanding when designing research studies
• Critically appraise research studies

• Access and extract relevant information from research publications
• Apply reporting guidelines to research studies and use critical appraisal tools
   

• Work collaboratively in a group
• Consider a range of different viewpoints
• Effectively communicate findings in presentations and written work
   

Formative feedback will primarily be provided in the face-to-face sessions.  Verbal feedback will be provided as part of facilitation of discussions and debates.  Feedback on student group presentations will include elements of both tutor feedback and peer feedback