STATS397-19B (HAM)

Work-Integrated Learning Directed Study

15 Points

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Division of Health Engineering Computing & Science
School of Computing and Mathematical Sciences
Department of Mathematics and Statistics


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Placement/WIL Coordinator(s)


Student Representative(s)

Lab Technician(s)



You can contact staff by:

  • Calling +64 7 838 4466 select option 1, then enter the extension.
  • Extensions starting with 4, 5, 9 or 3 can also be direct dialled:
    • For extensions starting with 4: dial +64 7 838 extension.
    • For extensions starting with 5: dial +64 7 858 extension.
    • For extensions starting with 9: dial +64 7 837 extension.
    • For extensions starting with 3: dial +64 7 2620 + the last 3 digits of the extension e.g. 3123 = +64 7 262 0123.
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Paper Description

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Students carry out an independent work-related project on an approved topic under staff supervision. This is done typically in collaboration with an external organisation who provide the project and the data for the student to work on. Depending on the arrangement, the student may have to work at the external organisation under the supervision of their staff.
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Paper Structure

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Students work on a real life project (often provided by the collaborating external organisation). This may involve, practical data analysis, literature review, self-study (or related methods, concepts, skills), computer programming or any other task necessary to complete the project. The students may spend time working off-site or on-campus depending on the requirements and the arrangements in place for each project.

Each project is likely unique and hence will have its own strucure.

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Learning Outcomes

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Students who successfully complete the course should be able to:

  • Apply the concerned data analytic skills on a real life data.
    Linked to the following assessments:
  • Summarize their findings in a report and effectively present them to an intelligent but general audience.
    Linked to the following assessments:
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The students will be assessed for their work on the project based on the quantity of the work carried out, the quality of the work and technical data analytic skills demonstrated. They will also be assessed on the project report they submit and the presentation they give based on that report. How effectively did the student manage to answer the question they set out to answer would be an important criterion too.
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Assessment Components

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The internal assessment/exam ratio (as stated in the University Calendar) is 100:0. There is no final exam. The final exam makes up 0% of the overall mark.

The internal assessment/exam ratio (as stated in the University Calendar) is 100:0 or 0:0, whichever is more favourable for the student. The final exam makes up either 0% or 0% of the overall mark.

Component DescriptionDue Date TimePercentage of overall markSubmission MethodCompulsory
1. Project report
21 Oct 2019
12:00 PM
  • Email: Convenor
2. Project presentation
  • In Class: In Workshop
Assessment Total:     100    
Failing to complete a compulsory assessment component of a paper will result in an IC grade
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Required and Recommended Readings

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Required Readings

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No specific required and recommended readings. These will vary for each project.
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Online Support

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This is work integrated learning and not a taught paper. Online learning methods are not typically applicable.
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The students are expected to work about 10 hours/week on the project and in total about 120 hours. The quantity and the quality of work carried out by the students must be consistent with this.
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Linkages to Other Papers

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Prerequisite papers: At least 45 points in Data Analytics at 200 level and permission of the Coordinator of the paper.




Restricted papers: STATS390, STATS391

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