Data Management & Statistical Computing

Subject POPH90018 (2010)

Note: This is an archived Handbook entry from 2010.

Credit Points:

12.50

Level:

9 (Graduate/Postgraduate)

Dates & Locations:

This subject has the following teaching availabilities in 2010:

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:

None

Coordinator

Prof John Carlin

Contact

Semester 1: Professor Cate D'Este & Mr Stephen Halpin, University of Newcastle
Semester 2: Dr Lyle Gurrin & Mr Kris Jamsen, University of Melbourne
Biostatistics Collaboration of Australia

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:	Topics include data management concepts, introduction to Stata and SAS, data management using Stata and SAS. Data management principles and concepts are developed using relational database software (Microsoft Access). Data manipulation, descriptive analyses and interpretation are introduced using SAS and Stata statistical software
Objectives:	The aim of this course is to introduce students to essential concepts and tools required for the management and analysis of data using modern statistical software. Students will also acquire skills in data display, summary presentation and pattern recognition using these tools.
Assessment:	Three written assignments to be submitted during semester, two worth 15% each (approx 6 hrs work each) and one worth 30% (approx 10 hrs work) One at-home examination at the end of Semester, worth 40% (approx 12 hrs work).
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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