Data Management and Statistical Computing

Description

This course will consider the impact of computers and the corresponding availability of data sets (often very large data sets) on the way we think about data and proceed to analyse and report on it. Includes sources of data, data storage, cleaning data, linking files, analysing large data sets and computer software. This course is offered in conjunction with the Biostatistics Collaboration of Australia (BCA).

Availability

Distance Education - Callaghan

  • Semester 1 - 2015
  • Semester 2 - 2015

Learning Outcomes

1. Be familiar with sources of data, issues in data entry, structure of data and data checking

2. Understand different methods of data storage such as unit records, matrix files, longitudinal data, use of relational databases and retrieving data, including data transfer, backup and security

3. Be experienced in cleaning of data, use of post data entry checks, validity of fields, outliers and data trimming

4. Be experienced in linking files through use of unique and non-unique identifiers

5. Be aware of the importance of confidentiality in data storage, management and analysis

6. Be experienced in the analysis of a variety of large data sets

7. Have experience in data manipulation and management using the major statistical software

Content

The course will be built around data sets obtained for different purposes, including routinely collected data. Content will include sources of data, data storage, cleaning data, linking files, analysing large data sets and computer software.

Requisites

This course is only available to students enrolled in the Graduate Diploma in Medical Statistics or Master of Medical Statistics programs.

Assessment Items

Written Assignment: Essays / Written Assignments

Contact Hours

Online Activity

Online 2 hour(s) per Week for Full Term

Delivered in distance learning mode only. Suggest 8-12 hours time commitment per week (guide only).

Self-Directed Learning

Self-Directed 6 hour(s) per Week for Full Term