Core Module Information
Module title: Predictive Analytics

SCQF level: 11:
SCQF credit value: 20.00
ECTS credit value: 10

Module code: SOE11167
Module leader: Max Chipulu
School The Business School
Subject area group: Management
Prerequisites

There are no pre-requisites for this module to be added

Description of module content:

Have you ever wondered how streaming companies know what movies and TV shows you will like? Or how do retailers know which products you will want to buy? It's all thanks to Predictive Analytics. Predictive Analytics is a way of using data to predict future events. Businesses and organizations of all types use Predictive Analytics to make better decisions. Here's a simple example:Imagine you're running a lemonade stand. You want to know how much lemonade to make on a given day. You could just guess, but wouldn't it be better to know with more confidence how many people will want lemonade? You could use predictive modelling to figure this out. You could use data like past sales numbers, the day of the week, and the weather forecast to predict how many people will want lemonade on a given day.Predictive Analytics can be used to predict all sorts of things, like:- How many people will attend a concert?- How many products a company will sell?- How much traffic there will be on a given road?- How likely a customer is to churn?- How likely a student is to succeed at university? etc.In this module, you will learn about different predictive analytics techniques and how to use them to help your organisation make more accurate decisions about future events.

Learning Outcomes for module:

Upon completion of this module you will be able to

LO1: Model and solve business decision problems using the appropriate predictive analytics techniques and software.

LO2: Demonstrate knowledge and understanding of the capabilities as well as limitations of predictive analytics techniques and have insight into the different fields in which we can usefully apply each.

LO3: Choose the most appropriate predictive analytics technique using various types of information criteria.

LO4: Interpret the results of predictive modelling analysis, including explaining margins of error and business implications.

Full Details of Teaching and Assessment

Indicative References and Reading List - URL:
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