UnitLevel 5Postgraduate

EPM5032 Applied health data analytics group case study

Faculty of Medicine, Nursing and Health Sciences

EPM5032 Applied health data analytics group case study is a level 5, 6-credit-point, postgraduate unit from the Faculty of Medicine, Nursing and Health Sciences. It isn't offered in 2023. It needs FIT9136, EPM5003, EPM5026, EPM5027, ETC5510, FIT5196, EPM5029, MPH5040, EPM5030 and (FIT5149 or ETC5250).

Credit points
6
Offered in 2023
Not offered
Assessment
No exam
5 tasks

This is the 2023 handbook entry. See the 2027 entry.

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Requisites

Overview

This unit will involve you working in a small team of three students to gain practical experience in health data analytics arising in an academic health research environment or industry.
Your team will be provided with a set of research questions from which one question will be allocated per team member.
You will work on answering your research question by applying the health data analytics process (visualisation, analysis, algorithms, etc.).
You will work closely together as a team using the project health research data to produce a team research report and infographic for each research question. You will be asked to reflect on your own learning as the team work progresses.

There are no lectures in this unit, although you will be expected to attend regular meetings with your team and tutor.

Offerings in 2023

The 2023 handbook lists no offerings for EPM5032.

Assessment

  • Teamwork project plan - 600 words (Team 100 words, Individual 500 words)Competency hurdle
    10%
  • Updated teamwork project plan (Individual - 900 words)
    15%
  • Project analysis plan (Individual - 900 words)
    15%
  • Case-study report and promotional communication - 2,700 words (Team 800 words, Individual 1,900 word
    45%
  • Reflection - 900 words (Individual 300 words at 3 assessments)
    15%

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    Elucidate strategies for answering research questions and associated health data analytical issues from a health or medical research dataset.

  2. 2

    Search, access and analyse research literature as part of the process of developing solutions to the health data analytics problems.

  3. 3

    Evaluate and select research methods and techniques of data preparation and analysis appropriate to a particular project, and practice these ethically and professionally.

  4. 4

    Collaborate effectively with other students in devising a strategy for analysis of the health research data, implementing the strategy and producing a report.

  5. 5

    Reflect on your work to describe your learning, how it changes at each stage, and how it might relate to future learning experiences.

  6. 6

    Communicate your analysis findings in a scientific written report and lay interpretation via an infographic.

Workload and teaching

Twelve hours per week, consisting of (on average)

  • 3 hours per week for reading relevant material
  • 8 hours per week working on the health data analytics (i.e. data wrangling, analysis, report writing)
  • 1-hour face-to-face meeting with team and tutor

No residential component is required.

Contacts

Chief Examiners
Dr Joanna Dipnall
Unit Coordinators
Dr Joanna Dipnall

Common questions

What are the prerequisites for EPM5032?

You need FIT9136, EPM5003, EPM5026, EPM5027, ETC5510, FIT5196, EPM5029, MPH5040, EPM5030 and (FIT5149 or ETC5250) before you enrol. Enrolment rules also apply.

When is EPM5032 offered?

EPM5032 has no offerings listed in the 2023 handbook.

Does EPM5032 have an exam?

No. EPM5032 has 5 assessment tasks and no exam.

More details

Credit points
6
Level
5
Study level
Postgraduate
Faculty
Faculty of Medicine, Nursing and Health Sciences
Organisational unit
Department of Epidemiology and Preventive Medicine
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 2
Study abroad
Not available
Handbook years
20232024202520262027