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Course profile

Data Management & Statistical Computing (STAT7603)

Study period
Sem 2 2024
Location
External
Attendance mode
Online

Course overview

Study period
Semester 2, 2024 (22/07/2024 - 18/11/2024)
Study level
Postgraduate Coursework
Location
External
Attendance mode
Online
Units
2
Administrative campus
Herston
Coordinating unit
Public Health School

STAT7603 introduces the software packages Stata and R, with the aim of providing a foundation to build upon in further studies and biostatistical career. The aim of this course 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.

This course is part of the Biostatistics Collaboration of Australia. If you are not enrolled in a Biostatistics program at UQ, please contact the Program Director, Dr Michael Waller, to seek permission before enrolling.

This course is part of the Biostatistics Collaboration of Australia (BCA). In this course we will develop statistical computing skills essential for managing and analysing data in health and medicine. This course provides an introduction to R and Stata, with the aim of giving you a foundation to build upon in your further studies and in your biostatistical career. ᅠ ᅠ

Further information about the course is available from the following link, ᅠᅠhttps://www.bca.edu.au/news/unit/data-management-and-statistical-computing-dmc/

Course contact

Course staff

Lecturer

Dr Michael Waller
Dr Nasir Moghaddar

Timetable

Additional timetable information

DMC is taught as a distance learning course, taught online through Canvas eLearning. For information on distance learning, see the Biostatistics Collaboration of Australia (BCA) distance learning site.


Module notes, data files, tutorial materials and other documents will be made available on eLearning. Assignments and course announcements will likewise be uploaded to eLearning.


Communication should generally be via the Discussion Board on eLearning (unless of a personal/confidential nature). You are encouraged to post questions, ideas, suggestions and discussions on eLearning. The Course Coordinator will monitor and respond to communication; however, you are encouraged to answer other students’ questions or assist in solving problems (with the exception of assignment question queries, which I will clarify).

Aims and outcomes

The aim of this unit 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

After successfully completing this course you should be able to:

LO1.

demonstrate skill in data manipulation and management using two major statistical software packages (Stata and R)

LO2.

display and summarise data using statistical software

LO3.

demonstrate skills in the checking and cleaning of data

LO4.

link data files through the use of unique and non-unique identifiers

LO5.

demonstrate fundamental programming skills for efficient use of software packages

LO6.

demonstrate understanding of key principles regarding confidentiality and privacy in data storage, management and analysis

Assessment

Assessment summary

Category Assessment task Weight Due date
Computer Code, Tutorial/ Problem Set Module 1 Assignment
  • Online
30%

16/08/2024 - 2/09/2024

Computer Code, Tutorial/ Problem Set Module 2 Assignment
  • Online
35%

13/09/2024 - 30/09/2024

Computer Code, Tutorial/ Problem Set Module 3 Assignment
  • Online
35%

18/10/2024 - 4/11/2024

Assessment details

Module 1 Assignment

  • Online
Mode
Written
Category
Computer Code, Tutorial/ Problem Set
Weight
30%
Due date

16/08/2024 - 2/09/2024

Learning outcomes
L01, L02, L03, L05

Task description

refer to Study Guide. Submission via DMC Canvas site.

Submission guidelines

Deferral or extension

You may be able to apply for an extension.

Please refer to the Policies and guidelines

Module 2 Assignment

  • Online
Mode
Written
Category
Computer Code, Tutorial/ Problem Set
Weight
35%
Due date

13/09/2024 - 30/09/2024

Learning outcomes
L01, L02, L03, L05, L06

Task description

refer to Study Guide. Submission via DMC Canvas site.

Submission guidelines

Deferral or extension

You may be able to apply for an extension.

Please refer to the Policies and guidelines

Module 3 Assignment

  • Online
Mode
Written
Category
Computer Code, Tutorial/ Problem Set
Weight
35%
Due date

18/10/2024 - 4/11/2024

Learning outcomes
L01, L02, L03, L04, L05, L06

Task description

refer to Study Guide. Submission via DMC Canvas site.

Submission guidelines

Deferral or extension

You may be able to apply for an extension.

Please refer to the Policies and guidelines

Course grading

Full criteria for each grade is available in the Assessment Procedure.

Grade Description
1 (Low Fail)

Absence of evidence of achievement of course learning outcomes.

Course grade description: (Typically 0-19%)

2 (Fail)

Minimal evidence of achievement of course learning outcomes.

Course grade description: (Typically 20-44%)

3 (Marginal Fail)

Demonstrated evidence of developing achievement of course learning outcomes

Course grade description: (Typically 45-49%)

4 (Pass)

Demonstrated evidence of functional achievement of course learning outcomes.

Course grade description: (Typically 50-64%)

5 (Credit)

Demonstrated evidence of proficient achievement of course learning outcomes.

Course grade description: (Typically 65-74%)

6 (Distinction)

Demonstrated evidence of advanced achievement of course learning outcomes.

Course grade description: (Typically 75-84%)

7 (High Distinction)

Demonstrated evidence of exceptional achievement of course learning outcomes.

Course grade description: (Typically 85-100%)

Supplementary assessment

Supplementary assessment is available for this course.

The final grade awarded will be based on the results of the supplementary assessment only, and a passing grade will be awarded if, and only if, the student receives at least 50% of the marks on the supplementary assessment. 

Additional assessment information

See the Study Guide for BCA policiesᅠregarding penalties for late submission. ᅠ



Learning resources

You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.

Library resources

Library resources are available on the UQ Library website.

Additional learning resources information

Other materials are set as required or supplementary readings in each module.ᅠ These cannot be uploaded to eLearning.ᅠ You can access the articles through your university’s library; further assistance in accessing readings will be given during the course.ᅠ

Learning activities

The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.

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Learning period Activity type Topic
Multiple weeks
Workshop

The basics

Importing and exporting data; recoding and formatting data; labelling variables and values; use of date data; displaying and summarising data. Construction of suitable programming scripts to reproduce results.

Learning outcomes: L01, L02, L03, L05

Workshop

Graphs, Data management and Quality Assessment

Includes advanced graphics for production of publication-quality graphs.

Learning outcomes: L01, L02, L03, L05, L06

Workshop

More Advanced Statistical Computing

Using functions to generate new variables, appending, merging and transposing data; programming skills including macros, loops, user-defined functions and programs.

Learning outcomes: L01, L02, L03, L04, L05, L06

Policies and procedures

University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:

Learn more about UQ policies on my.UQ and the Policy and Procedure Library.

Course guidelines

School of Public Health (SPH) Guidelines for late submission of progressive assessment - Preamble

To apply for an extension to the due date for a piece of progressive assessment (eg assignments, oral presentations and computer-based assignments) students should complete the online request at  https://my.uq.edu.au/node/218/1 

Information regarding deferral of in-semester exams and end-of-semester exams is available from https://my.uq.edu.au/information-and-services/manage-my-program/exams-and-assessment/deferring-exam 

If requesting an extension on medical grounds, a medical certificate must be provided. The extension will be approved for the number of days included in the medical certificate that the student was not fit to study or work, eg if the medical certificate is for 3 days, an extension will be approved for 3 days maximum regardless of the student's request.  

If requesting an extension using a Student Access Plan for Disability (SAPD) as evidence, a maximum of 7-day extension will be approved in the first instance. Updated medical documentation, as well as a copy of the SAPD, is required if requesting an extension for more than 7 days. 

The maximum time for an in-semester extension is four weeks.  

The following SPH guidelines are consistent with the UQ policy. However, the SPH Guidelines contain specific rules and interpretations for SPH courses, and requests for extension and penalties for late submissions will be judged according to the guidelines outlined in this document. You should read both the information in your my.UQ at the following link: https://my.uq.edu.au/information-and-services/manage-my-program/exams-and-assessment/applying-assessment-extension?p=1#1 and the SPH guidelines (below) before submitting a request for an extension. The SPH Guidelines apply to all courses offered by the School of Public Health unless the ECP explicitly states otherwise.

SPH Guidelines for late submission of progressive assessment

Initial extension for an individual item of assessment – the SPH Teaching & Assessment Support Team and/or the Course Coordinator decides.

This could be for medical or compassionate reasons, or if, in the opinion of the Course Coordinator, there are exceptional circumstances.

Acceptable and unacceptable reasons for an extension are listed at the following link, along with the required evidence to be provided: https://my.uq.edu.au/information-and-services/manage-my-program/exams-and-assessment/applying-assessment-extension?p=1#1 

All requests should be lodged at least 24 hours prior to the due date for the assessment.

If applying for an extension after the due date and time of the assessment item, your request may not be approved. An explanation as to why your request was not submitted prior must be included.       

If approved, a new due date will be set. This would generally be no later than 7 days after the original due date, however this can be modified to take account of the circumstances of the request and the time that would have been lost from studies.

If the new due date is past the date for submission of end-of-semester results, the student will receive an INC (incomplete) result.

Second and all subsequent extensions for an individual item of assessment – the SPH Teaching & Assessment Support Team and/or the Program Director together with the Course Coordinator decides.

This would only be approved for exceptional circumstance with supporting documentation.

  • Online requests must be made at least 24 hours prior to the due date from the first extension.
  • The SPH Teaching & Assessment Support Team and/or the Course Coordinator will consult with the Program Director, who will make the final decision.
  • If approved, the new due date would generally be no later than 7 days after the first extension due date.
  • The Program Director should consider if remedial or other support should be offered to the student.
  • The Program Director should provide a report on these matters as needed at SPH Examiners’ Meetings.

Please Note: In order to support course progression, extensions that total more than 14 calendar days from the original due date of an assessment item will only be approved in very exceptional circumstances. These requests are assessed and approved or denied on a case-by-case basis. 

If you have been ill or unable to attend class for more than 14 days, we advise you to carefully consider whether you are capable of successfully completing your courses this semester. You might be eligible to withdraw without academic penalty.

Penalty for late submission

Submission of assignments, practical reports, workbooks, and other types of written assessments after the due date specified in the Electronic Course Profile (ECP) will receive a penalty.

The penalty will be a deduction of 10% RELATIVE PERCENTAGE per day (24 hour period or part thereof, including weekends and public holidays) or for work graded on a 1-7 scale, a deduction of one grade per day, e.g If the original mark is 73%, then 10% relative percentage is 10% of this value, ie 7.3%, The final mark for this assessment item after applying the penalty for 1 day late submission would be 73 -7.3 = 65.7% The same outcome is achieved by multiplying the original score by .9; ie 73 x .9 = 65.7%

The penalty for multiple days late is the relative percentage multiplied by the number of days late. 

A submission that is not made within 10 days of the due date will receive a mark of 0% for that assessment item.

Where a student has sought more than one extension, the due date for calculating the penalty will be the due date for the most recently approved extension.

Submission of Medical Certificates

Students are responsible for ensuring that any medical documentation they submit is authentic and signed by a registered medical practitioner. Such practitioners can be identified via the AHPRA website. Also note that:

  • Not all online medical services are staffed by registered practitioners
  • If the registration status of the practitioner cannot be verified, then an alternative practitioner should be sought
  • Students will be held fully responsible for all documentation they submit, even if done so in ignorance of the practitioner's registration status

Medical documentation may be subjected to an audit by the University.

 

School of Public Health (SPH) Assessment Guidelines

The School of Public Health assessment tasks have been designed to be challenging, authentic and complex. While students may us AI technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.

A failure to reference AI use may constitute student misconduct under the Student Code of Conduct.

To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI tools.