Data Management & Statistical Computing

Subject POPH90018 (2012)

Note: This is an archived Handbook entry from 2012.

Credit Points: 12.50
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2012:

Semester 1, Parkville - Taught online/distance.
Pre-teaching Period Start not applicable
Teaching Period not applicable
Assessment Period End not applicable
Last date to Self-Enrol not applicable
Census Date not applicable
Last date to Withdraw without fail not applicable

Semester 2, Parkville - Taught online/distance.
Pre-teaching Period Start not applicable
Teaching Period not applicable
Assessment Period End not applicable
Last date to Self-Enrol not applicable
Census Date not applicable
Last date to Withdraw without fail not applicable

Distance only



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

8-12 hours total study time per week

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.

Coordinator

Prof John Carlin

Contact

Semester 1: Dr Patrick McElduff, University of Newcastle
Semester 2: Professor John Carlin, Melbourne School of Population Health, University of Melbourne

Biostatistics Collaboration of Australia
Email: bca@ctc.usyd.edu.au
Website: www.bca.edu.au

OR

Academic Programs Office
Melbourne School of Population Health
Tel: +61 3 8344 9339
Fax: +61 3 8344 0824
Email: sph-gradinfo@unimelb.edu.au

Subject Overview:

Relational databases and how to explore them using Stata and SAS; using Stata and SAS to import, check, inspect and manipulate data, including appending, merging, using dates, transposing longitudinal data; fundamental programming skills for efficient and reproducible use of these packages, including loops, arguments and programs/macros; data display and summary presentation, including advanced graphics to produce publication-quality graphs.

Objectives:

The aim of this course is to introduce students to essential concepts and tools required for the management, manipulation, display and analysis of data using the Stata and SAS statistical software packages.

Assessment:

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:

Cody, R., Smith, J. Applied Statistics and the SAS Programming Language, 5th edition, Prentice-Hall, 2005. (ISBN 0131465325)
Hills, M and De Stavola, B, A Short Introduction to Stata for Biostatistics, Timberlake, 2006. – order online at www.survey-design.com.au

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: www.bca.edu.au/student_info.htm

Recommended Texts:

None

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: http://www.sph.unimelb.edu.au
Notes:

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

Related Course(s): Master of Biostatistics
Postgraduate Certificate in Biostatistics
Postgraduate Diploma in Biostatistics

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