Data Management & Statistical Computing

Subject POPH90018 (2016)

Note: This is an archived Handbook entry from 2016.

Credit Points: 12.5
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2016:

Semester 1, Parkville - Taught online/distance.
Pre-teaching Period Start not applicable
Teaching Period 29-Feb-2016 to 29-May-2016
Assessment Period End 24-Jun-2016
Last date to Self-Enrol 11-Mar-2016
Census Date 31-Mar-2016
Last date to Withdraw without fail 06-May-2016

Semester 2, Parkville - Taught online/distance.
Pre-teaching Period Start not applicable
Teaching Period 25-Jul-2016 to 23-Oct-2016
Assessment Period End 18-Nov-2016
Last date to Self-Enrol 05-Aug-2016
Census Date 31-Aug-2016
Last date to Withdraw without fail 23-Sep-2016

This subject is only available to students who are currently enrolled in the Graduate Diploma or Master of Biostatistics and whose enrolment in that course commenced prior to 2016.

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: None
Total Time Commitment:

170 hours

Prerequisites: None
Corequisites: None
Recommended Background Knowledge: None
Non Allowed Subjects: None
Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements of this entry.
The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website.


Prof John Carlin


Melbourne School of Population and Global Health


Currently enrolled students:

Future Students:

Subject Overview:

The aim of this subject is to provide students with the knowledge and skills required to undertake moderate to high level data manipulation and management in preparation for statistical analysis of data typically arising in health and medical research.

Learning Outcomes:

Specific objectives are for students to:

  • Gain experience in data manipulation and management using two major statistical software packages (Stata and SAS)
  • Learn how to display and summarise data using statistical software
  • Become familiar with the checking and cleaning of data
  • Learn how to link files through use of unique and non-unique identifiers
  • Acquire fundamental programming skills for efficient use of software packages
  • Learn key principles regarding confidentiality and privacy in data storage, management and analysis


Three written assignments to be submitted during semester, one worth 30% (approx 10 hrs work) and two worth 35% each (approx 12 hrs work each).

Prescribed Texts:

Resources Provided to Students: Printed course notes and assignment material provided by mail and email, and onine interaction facilities.

Special Computer Requirements: SAS AND Stata software as well as Microsoft Access. For advice about purchasing these packages (education license prices); see “Study Resources” at:

Recommended Texts:

If you have not used SAS or Stata previously, it is recommended that you have access to the text for the relevant software:
Cody R, Smith J. Applied Statistics & the SAS Programming Language. 5th edition. Prentice Hall 2006. ISBN 9780131465329
Hills M, De Stavola B. A Short Introduction to Stata for Biostatistics updated to Stata 12. London: Timberlake Consultants Ltd, 2012. ISBN 9780957170803.

Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

Independent problem solving, clarity of written expression, sound communication of technical concepts

Links to further information:

This subject is not available in the Master of Public Health.

Related Course(s): Graduate Certificate in Biostatistics
Postgraduate Diploma in Biostatistics

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