This unit entry is for students who completed this unit in 2016 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

EPM5005 - Data management and statistical computing

6 points, SCA Band 2, 0.125 EFTSL

Postgraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.

Faculty

Medicine, Nursing and Health Sciences

Organisational Unit

Department of Epidemiology and Preventive Medicine

Coordinator(s)

Professor Patrick McElduff

Offered

Alfred Hospital

First semester 2016 (Off-campus)
Second semester 2016 (Off-campus)

Synopsis

This unit will describe and demonstrate the complexity of data management and statistical computing methods. It will enable students to communicate effectively about the issues in storing and retrieving information, and in assessing the quality and limitations of data repositories. It uses examples from real data sets to give students practical skills in data management, assessment of data quality and handling and linking of large volumes of data.

Outcomes

Upon successful completion of this unit, students should be able to have:

Understanding of different sources and methods of data storage such as unit records, matrix files, longitudinal data, relational databases.
Understanding of relational database concepts and data retrieval methods.
Proficiency in the handling and analysis of large data sets.
Skills in data manipulation and management using the major statistical software packages.
Skills in linking files through unique and non-unique identifiers.
Understanding of data quality control and data entry methods and confidentiality issues, and experience in applying validation checks to data.
Skills in data cleaning, identification of outliers and data trimming using appropriate statistical methods.
Understanding of processes leading to finalisation of data sets prior to analysis.
Ability to communicate with researchers in data-related issues of design, conduct and analysis of studies.