MIS3003S Business Analytics

Academic Year 2019/2020

Business Analytics focuses on the use of mathematical, statistical,
data-oriented and computer-based techniques to help businesses operate
optimally. It seeks to understand what has happened and predicting
what is going to happen, and making optimal decisions to take
advantage of that.

The main techniques we consider are Correlation, Regression,
Time-Series Forecasting, Linear Programming, Classification, and
Clustering. For each technique we study, we learn how it works on
paper before proceeding to software-based implementations. We also
consider practical applications of these techniques, including some or
all of sales forecasting, credit risk, resource allocation, employee
assignment, investment, customer churn, inventory, and product mix.

Emphasis is placed not only on formulating and using models to obtain
solutions, but on understanding case study problems, choosing the
appropriate models, and interpreting and critiquing the results.

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Curricular information is subject to change

Learning Outcomes:

On completion of this module, students should be able to understand a
range of quantitative business problems and identify suitable
analytics models for addressing them; and be able to explain, carry
out in practice, and interpret the results of models including
regression, time series forecasting, correlation, linear programming,
classification, and clustering.

Student Effort Type Hours
Lectures

20

Specified Learning Activities

85

Autonomous Student Learning

110

Total

215

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.  
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Examination: Examination 2 hour End of Trimester Exam No Graded No

60

Assignment: Main Assignment Varies over the Trimester n/a Graded No

40


Carry forward of passed components
No
 
Resit In Terminal Exam
Spring Yes - 2 Hour
Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

General feedback is provided to students on all their submitted assessment components.

Name Role
Ms Christina Burke Tutor
Mr Neil Caraher Tutor
Miss Clare Griffin Tutor
Dr Sean McGarraghy Tutor
Dr Miguel Nicolau Tutor
Rachel Sim Tutor
Chee Shong Tan Tutor
Charlene Tan Puay Koon Tutor
Siti Zarifah Tutor

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