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Predictive Analytics (BISY90016)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Overview
Availability(Quotas apply) | April |
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Fees | Look up fees |
Predicting key business variables has become increasingly important, as it drives both objective decision-making and improved profitability within organisations. This subject covers the main methods used to predict business variables, based on historical data. These include traditional regression, time series analysis, forecasting models, survival analysis, data mining, support vector machines and sentiment analysis. Throughout the subject, the focus will be on understanding how these methods are applied in various business problems, and identifying which predictive approach is the most appropriate to use, given a specific context. The importance of benchmarking different methodologies, as well as the use of prediction in decision-making frameworks, will also be emphasised.
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
Enrolled in one of the Master of Business Administration courses and completion of 112.5 credit points of core subjects in the courses
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
Individual assignment (1,000 words)Week 520%Syndicate assignment (equivalent to individual 1,000 words assessment) Week 830%Final examination (3 hours, hurdle requirement) End of term 50%Last updated: 3 November 2022
Quotas apply to this subject
Dates & times
- April
Mode of delivery On Campus (Parkville) Contact hours 30 hours Total time commitment 150 hours Pre teaching start date 2 April 2018 Pre teaching requirements students are required to complete approximately 20 hours of reading during pre-teaching period to prepare for the subject Teaching period 9 April 2018 to 14 June 2018 Last self-enrol date 4 February 2018 Census date 20 April 2018 Last date to withdraw without fail 25 May 2018 Assessment period ends 21 June 2018
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
Last updated: 3 November 2022