Predictive and Prescriptive Analytics - BUSN7940

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2024 to 2025
Canterbury
Autumn Term 6 15 (7.5) Ricky Mak checkmark-circle

Overview

Business analytics isn't only concerned with understanding data, it's about transforming data into actions through your unique analysis and insights. Predictive and prescriptive analytics are the most important analysis tools in business today. We’ll make you an expert in both, through mastering the fundamentals and getting hands-on experience using software such as SPSS and Excel to find solutions for case studies, you’ll be ready to bring your analysis to real world scenarios.

Details

Contact hours

Total contact hours: 21
Private study hours: 129
Total study hours: 150

Method of assessment

Main assessment methods
In-Course Test 1, 45 minutes (20%)
In-Course Test 2, 45 minutes (20%)
Individual computer based report (2000 words) (60%)

Reassessment methods
100% coursework

Indicative reading

Albright S. and Winston W.L. (2016). Business Analytics: Data Analysis & Decision Making (6th Ed). Boston, MA: Cengage.

Evans, J. R. (2013). Business Analytics. Methods, Models and Decisions. Harlow: Pearson Education.

Winston, W.L. (2004). Operations Research: Applications and Algorithms (4th Ed.), Belmont, MA: Duxbury Press.

See the library reading list for this module (Canterbury)

Learning outcomes

The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
- Use predictive and prescriptive analytic techniques to handle a variety of business problems.
- Apply regression analysis and forecasting techniques to characterise relationships among business variables, identify patterns in data and predict future trends.
- Build and solve linear optimisation models and interpret their results for effective decision making
- Develop a systematic understanding of different types of optimisation models and how they can be applied in practice to solve problems in different business contexts

The intended generic learning outcomes.
On successfully completing the module students will be able to:
- Use a variety of scientific approaches to build and solve models for a range of practical management problems.
- Analyse the models and be able to make recommendations based on that analysis.
- Demonstrate an ability to select the most appropriate solution technique for particular problems.
- Plan work and study independently using relevant resources.

Notes

  1. Credit level 6. Higher level module usually taken in Stage 3 of an undergraduate degree.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
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