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  3. Predictive Analytics

Predictive Analytics (BISY90016)

Graduate courseworkPoints: 12.5On Campus (Parkville)

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Overview

Year of offer2019
Subject levelGraduate coursework
Subject codeBISY90016
Campus
Parkville
Availability(Quotas apply)
September
FeesSubject EFTSL, Level, Discipline & Census Date

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: 11 November 2018