Studying online

There are now 2 possible online modes for units:

Units with modes Online timetabled and Online flexible are available for any student to self-enrol and study online.

Click on an offering mode for more details.

Unit Overview

Description

This unit will introduce students to data analytics in the large and growing health sector. There is an increasing demand to make sense of the large quantities of health data readily available in both the public and private health sector to improve decision making and policy design. This unit provides an understanding of the range of methods used by health economists and professionals for the statistical analysis of survey data. There is a strong emphasis on applications, illustrating the use of relevant computer software applied to large scale data sets.

The purpose of the unit is to provide a practical guide to the analysis of health data that is built around a series of case studies based on recent health economics research. The unit is divided into 5 key parts. The first part focuses on health measures and describing and summarising health data. The second part introduces the multivariate analysis of health survey data and issues of how to identify causal effects from empirical data. The third part introduces health equity and the estimation of heterogeneous effects across different subpopulations. The fourth part moves from cross-sectional to longitudinal data, introducing applications with linear and non-linear panel data regression models. Part five turns to methods that are suitable for modelling individual data on health care utilisation when that is measured by the number of visits or by levels of expenditure.

Credit
6 points
Offering
(see Timetable)
AvailabilityLocationMode
Semester 2UWA (Perth)Face to face
Outcomes

Students are able to (1) demonstrate an understanding of the concept of health and its measurement; (2) describe and visualise health data; (3) estimate a range of statistical models and techniques specific to measures of health and health care; (4) interpret statistical findings in a critical and rigorous manner; and (5) communicate statistical findings in a clear and concise manner and communicate them to non-technical audiences.

Assessment

Indicative assessments in this unit are as follows: (1) data visualisation assessment; (2) research report assessment; and (3) quizzes and participation. Further information is available in the unit outline.



Student may be offered supplementary assessment in this unit if they meet the eligibility criteria.

Unit Coordinator(s)
Dr Michael Palmer
Unit rules
Prerequisites
Enrolment in
CM002 Bachelor of Economics and Master of Economics
or 42620 Master of Economics
or 42670 Master of Economics
or 42630 Master of Business Analytics
or 42580 Master of Public Policy
or 62530 Master of Data Science
Contact hours
seminars: up to 3 hours per week for 12 weeks
  • The availability of units in Semester 1, 2, etc. was correct at the time of publication but may be subject to change.
  • All students are responsible for identifying when they need assistance to improve their academic learning, research, English language and numeracy skills; seeking out the services and resources available to help them; and applying what they learn. Students are encouraged to register for free online support through GETSmart; to help themselves to the extensive range of resources on UWA's STUDYSmarter website; and to participate in WRITESmart and (ma+hs)Smart drop-ins and workshops.
  • Visit the Essential Textbooks website to see if any textbooks are required for this Unit. The website is updated regularly so content may change. Students are recommended to purchase Essential Textbooks, but a limited number of copies of all Essential Textbooks are held in the Library in print, and as an ebook where possible. Recommended readings for the unit can be accessed in Unit Readings directly through the Learning Management System (LMS).
  • Contact hours provide an indication of the type and extent of in-class activities this unit may contain. The total amount of student work (including contact hours, assessment time, and self-study) will approximate 150 hours per 6 credit points.