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Exploratory Data Analysis and Visualisation (11374.1)

Level: Level 3 - Undergraduate Advanced Unit
Credit Points: 3
HECS Bands: 2
Faculty: Faculty of Science and Technology
Discipline: Academic Program Area - Technology


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For the remainder of 2020, resulting from Australian Government's directives requiring physical distancing and restrictions on movement because of the COVID-19 pandemic, any exams that are required for assessment in a unit will be online exams. Online exams may also use online proctoring to help assure the academic integrity of those exams. Please contact your unit convener with any questions.

While the University has made efforts to ensure that Unit Outlines reflect a unit’s learning activities and assessment items, any changes to Australian Government directives because of the COVID-19 pandemic may require changes to these during the semester to ensure the safety and well being of students and staff. These changes will not be updated in the published unit outline, but will be communicated to you via your unit’s UCLearn(Canvas) teaching site. Any changes made will continue to meet the unit’s learning outcomes, as described in the Unit Outline.

Unit Outlines

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  • Semester 1, 2020, ON-CAMPUS, BRUCE (198590) - View

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Data and its analysis and modelling underpin all aspects of work and society in the 21st century. This unit provides students with a thorough study exploratory data analysis and visualisation techniques. Exploratory Data Analysis is an approach to data analysis that employs a variety of techniques, mostly graphical. The main role of this approach is to open-mindedly explore the data. Visualisation enables the data to reveal its structural secrets and provide new insight into the data. Exploratory Data Analysis allows the data scientist to discover patterns, to spot anomalies, to test hypothesis and to check assumptions with the help of summary statistics and graphical representations. This unit will provide hands-on experience in data visualisation and summary statistics using real-world data examples.

Learning Outcomes

After successful completion of this unit, students will be able to:

1. Choose and apply the most suitable techniques for exploratory data analysis;

2. Map out the underlying structure of the data;

3. Detect anomalies and missing data; and

4. Demonstrate competent skills in using visualisation techniques for analysis and communication.

Assessment Items

Contact Hours

Four hours of on campus classes including problem-based learning activities, interactive workshops and practical laboratory work.


Must have passed 24 credit points.



Assumed Knowledge

Working knowledge of discrete mathematics, algebra and numerical analysis.

Incompatible Units

11517 Exploratory Data Analysis and Visualisation G

Equivalent Units


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