BUS3061 : Business Analytics (Inactive)

Semester 1 Credit Value: 10
Semester 2 Credit Value: 10
ECTS Credits: 10.0


In today’s technology led world, businesses, government, and individuals are generating immense collections of data as part of their routines. Increasingly, managers are constantly facing decisions and having to rely on these data to optimise and streamline their operations. Therefore, the ability to collect, analyse, and interpret vast amounts of data becomes undeniably important. This module aims to introduce the students to major concepts in business analytics. By combining statistics and mathematical methods, students will be equipped with the invaluable skills in exploring real-world data to find patterns and relationships and use them to make informed decisions. They will also be able to explain some businesses phenomenon through statistical analysis and validate their decisions. Finally, the students completing this module will have good commands of time series analysis techniques and forecasting methods.

Outline Of Syllabus

* Introduction to business analytics
* Data mining and data mining processes
* Multivariate statistics
* Forecasting and time series models
* Model analytics

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion159:0059:00N/A
Scheduled Learning And Teaching ActivitiesLecture123:0036:00N/A
Guided Independent StudyDirected research and reading147:0047:00N/A
Scheduled Learning And Teaching ActivitiesWorkshops81:008:00N/A
Guided Independent StudyIndependent study150:0050:00N/A
Teaching Rationale And Relationship


Assessment Methods

The format of resits will be determined by the Board of Examiners

Description Length Semester When Set Percentage Comment
Written Examination1802A80Individual/ unseen exam questions
Other Assessment
Description Semester When Set Percentage Comment
Computer assessment1M20Individual/ unseen exam questions
Assessment Rationale And Relationship


Reading Lists