Handbook home
Critical Thinking with Analytics (MAST90130)
Graduate courseworkPoints: 12.5Online
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Term 1
Melbourne School of Professional and Continuing Education
Further information: https://study.unimelb.edu.au/find/courses/graduate/master-of-applied-analytics
Email: continuing-education@unimelb.edu.au
Phone: + 61 3 8344 0149
Monday to Friday 8am to 9pm AEST/AEDT. Weekends and University of Melbourne observed Public Holidays 10am to 5pm AEST/AEDT.
Term 3
Melbourne School of Professional and Continuing Education
Further information: https://study.unimelb.edu.au/find/courses/graduate/master-of-applied-analytics
Email: continuing-education@unimelb.edu.au
Phone: + 61 3 8344 0149
Monday to Friday 8am to 9pm AEST/AEDT. Weekends and University of Melbourne observed Public Holidays 10am to 5pm AEST/AEDT.
Overview
Availability | Term 1 - Online Term 3 - Online |
---|---|
Fees | Look up fees |
Introduction to the principles and practice of dealing with data, including measurement scales, data organisation, summaries, study design and inference. Students will learn how to think critically about the use of data in the public and private sectors, and appraise how results and analyses are presented by outlets such as the media. Emphasis will focus on interpretation and understanding of the appropriate use of data rather than the technical details of performing the analysis.
Intended learning outcomes
On completion of this subject, students will be able to:
- Distinguish different types of data used in different forms of research evidence and describe the important contextual elements of data in providing good research evidence.
- Classify scales used in data by using the principles of measurement to recognise important variations in data and to identify its sources.
- Explain the main types of study designs in data analytics and justify the choice of a study design for a specified purpose. Explain the main types of study designs in data analytics, i.e. an experiment, a survey and an observational study and justify the choice of a study design for a specified purpose
- Examine a data set and design a systematic approaches to managing it using descriptive analysis, as well as tools for representing and summarising data, and visualising the data.
- Identify applicable probabilistic structures and their associated risks, in given data analytics scenarios, through knowledge of the role of probability and risk in the framework of data analytics and of the different risk assessment approaches.
- Identify and distinguish the circumstances under which elementary probability models for data would be used.
- Critique the use of confidence intervals, hypothesis tests and other representations of inference in real-world applications of data analytics based on an understanding of the basic paradigms for inference from data.
- Appraise the use of data in a public forum, especially the media, and formulate a critique of data-based reasoning that is used.
Generic skills
Students will be provided with the opportunity to practice and reinforce:
- High level written communication skills.
- Interpretation skills.
- Demonstrate competence in critical and theoretical thinking through essay writing and online discussions.
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
It is expected that students will already be familiar with basic concepts from statistics and probability.
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: 3 November 2022
Assessment
Additional details
- Contribution to online discussions. Assessment will be based on participation. 500 words in total, due throughout the semester, 10%
- Two concise essays to appraise the use of data in a study, public debate and official report, each 300 words. Students will be assessed based on their understanding and critique of the methods of design, analysis, and inference, and their discussion of the validity of the results. Due end of weeks 3 and 5, 600 words in total, due throughout the semester, 15%
- Formative online tests. To include multiple choice and short answer questions to assess understanding of the analytics concepts. End of weeks 2, 6 and 8, 1,250 words in total, 35%
- Case study written assignment. Students will be assessed based on their detailed understanding and critique of the methods of design, analysis, and inference, and their discussion of the validity of the results. 2,500 words, week 9 - during assessment period, 40%
Last updated: 3 November 2022
Dates & times
- Term 1 - Online
Principal coordinator Ian Gordon 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 28 January 2019 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 4 February 2019 to 31 March 2019 Last self-enrol date 29 January 2019 Census date 22 February 2019 Last date to withdraw without fail 15 March 2019 Assessment period ends 7 April 2019 Term 1 contact information
Melbourne School of Professional and Continuing Education
Further information: https://study.unimelb.edu.au/find/courses/graduate/master-of-applied-analytics
Email: continuing-education@unimelb.edu.au
Phone: + 61 3 8344 0149
Monday to Friday 8am to 9pm AEST/AEDT. Weekends and University of Melbourne observed Public Holidays 10am to 5pm AEST/AEDT.
- Term 3 - Online
Principal coordinator Ian Gordon 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 15 July 2019 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 22 July 2019 to 15 September 2019 Last self-enrol date 16 July 2019 Census date 9 August 2019 Last date to withdraw without fail 30 August 2019 Assessment period ends 22 September 2019 Term 3 contact information
Melbourne School of Professional and Continuing Education
Further information: https://study.unimelb.edu.au/find/courses/graduate/master-of-applied-analytics
Email: continuing-education@unimelb.edu.au
Phone: + 61 3 8344 0149
Monday to Friday 8am to 9pm AEST/AEDT. Weekends and University of Melbourne observed Public Holidays 10am to 5pm AEST/AEDT.
Time commitment details
170
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
Students will have access to electronic copies of relevant readings
Last updated: 3 November 2022