Handbook home
Foundations of Analytics (MAST90135)
Graduate courseworkPoints: 12.5Online
From 2023 most subjects will be taught on campus only with flexible options limited to a select number of postgraduate programs and individual subjects.
To learn more, visit COVID-19 course and subject delivery.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Term 4
Email: continuing-education@unimelb.edu.au
Phone: + 61 3 8344 0149
Contact hours: https://unimelb.edu.au/professional-development/contact-us
Overview
Availability | Term 4 - Online |
---|---|
Fees | Look up fees |
The Foundations of Analytics is a core subject in the Health specialisation. It looks at the foundational principles and practice of modern data analytics, including techniques of data manipulation, presentation, and analysis. It’s teaching approach will emphasis interpretation underpinned by an understanding of the appropriate use of data, rather than just disseminating the technical details about performing an analysis. Students will be introduced to probability models used for a continuous response and will learn how to use methods such as linear models, tree-based methods and forecasting. Students will also use statistical software to analyse data.
Intended learning outcomes
On completion of this subject, students will be able to:
- Apply basic methods to organise a data set for analysis, including importing into statistical software, cleaning, coding and arranging data
- List the important types of analytics software and use at least two different software packages to perform some basic analyses
- Expand on the graphics material in "Critical Thinking with Analytics" to develop more sophisticated graphics, including panel graphs
- Develop a taxonomy of graphical forms and apply it to different graphical requirements
- Assess and critique modern data visualisations
- Identify and describe several of the main forms of probability models used for description, analysis and forecasting of data, including simple analyses and models, the general linear model, models in forecasting and tree-based models
- Apply simulation methods to address a non-standard analytics problem
- Evaluate and critique the use of analytics in case studies and apply sound principles to create a high-level design for an analytics investigation
Generic skills
Students will be provided with the opportunity to practise and reinforce:
- High level written communication skills.
- Interpretation skills.
- Demonstrate competence in critical and theoretical thinking through essay writing and online discussions.
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST90130 | Critical Thinking with Analytics |
Term 1 (Online)
Term 3 (Online)
|
12.5 |
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 31 January 2024
Assessment
Description | Timing | Percentage |
---|---|---|
Contribution to online discussions. Assessment will be based on participation.
| Throughout the semester | 10% |
Three concise essays to appraise the analytics used in a study, public debate and official report, each 300 words. . Students will be assessed based on their understanding and critique of the methods, and their discussion of the validity of the results. Due end of weeks 2, 4 and 6.
| Throughout the semester | 15% |
Short answer online test To include multiple choice questions to assess understanding of the analytics concepts.
| Week 7 | 35% |
Case study written assignment. Case study written assignment (2500 words. Students will be assessed based on their detailed understanding and critique of the methods, and their discussion of the validity of the results. Additionally, students should be able to perform their own analysis using techniques developed in the subject.
| End of term | 40% |
Last updated: 31 January 2024
Dates & times
- Term 4 - Online
Coordinator Sue Finch Mode of delivery Online Contact hours 3-4 hours per week, including online lectures, discussion forums and other resources Total time commitment 170 hours Pre teaching start date 10 October 2022 Pre teaching requirements During the pre-teaching period students are given the opportunity to get used to the online platform, meet the instructors/tutors and become familiar with how to access resources before the teaching period starts. Teaching period 17 October 2022 to 11 December 2022 Last self-enrol date 11 October 2022 Census date 4 November 2022 Last date to withdraw without fail 25 November 2022 Assessment period ends 18 December 2022 Term 4 contact information
Email: continuing-education@unimelb.edu.au
Phone: + 61 3 8344 0149
Contact hours: https://unimelb.edu.au/professional-development/contact-us
Last updated: 31 January 2024
Further information
- Texts
Prescribed texts
Students will have access to electronic copies of relevant readings
Last updated: 31 January 2024