LUBS5308M01 Business Analytics and Decision Science
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LUBS5308M01
Business Analytics and Decision Science
100% Assignment
This assignment contains two parts which are both equally weighted:
Part 1 (50% marks – 1,500 words maximum):
As a consultant for a major international car manufacturing company, you have been asked to help
decide on which prototype technology to develop for a new car powertrain. You have been
approached by the car company to help model the decision using the Analytic Hierarchy Process (AHP)
and TOPSIS based on five criteria; development cost, expected carbon emissions, engine efficiency,
car acceleration, and the maximum speed in miles per hour. There are four alternatives of powertrain
technology: electric, hydrogen, hybrid, and petrol.
LUBS5308M01
Using this information model this decision using AHP and TOPSIS. You will have to make assumptions
based on the information provided to create the decision tables for AHP and TOPSIS. Your report has
two objectives:
1. Summarise the data used and outputs for the AHP and TOPSIS analyses, including your
workings in a single Excel file.
2. Respond to the car company on how to proceed with their decision. Provide justification for
your response using your analyses.
Your (1,500 word maximum) report should use tables and figures as appropriate as well as text to
present your findings. In addition to the report, you must submit all your workings/calculations in a
single Excel file. This Excel file must contain no annotations, all written work should be in the report.
No appendices are required, and any material provided in appendices will not contribute to the final
mark. This section will be marked using the following marking scheme:
Success Criteria Weighting
General
Presentation
Use of tables and graphics
Introduction
AHP and TOPSIS analyses
Identifying and summarising the data used
Providing and describing the outputs of the analyses
Response to Company
Summary of the way forward for the company
Technical details on how you came to give this advice
15%
5%
10%
10%
35%
15%
20%
40%
20%
20%
Total = 100%
Note: Presentation includes structure/format of the report, clarity of expression, grammar, and
spelling. Your report will be rated on each success criterion using a six-point scale from 0 (very poor)
to 5 (excellent). The overall mark will be a weighted average of the ratings.
LUBS5308M01
Part 2 (50% marks - 1,500 words maximum):
A computer part retailer has approached you to find an innovative way of recommending central
processing unit (CPU). They have provided you with data on 74 different CPUs which have the
following columns (Q2Data.csv):
Name: CPU’s Name
Core Count: Number of Processor Cores
Core Clock: Base Speed of Processor Cores
Boost Clock: Boost Speed of Processor Cores
TDP: Thermal design power (watts)
Integrated Graphics: Does it have integrated graphics? (Yes/No)
Simultaneous multithreading: Does it have ability to do simultaneous multithreading?
Price: The price of the CPU
The retailer has asked you to group the 74 processors into unique clusters that can be recommended
to customers based on the attributes provided. The company will use the cluster information for
marketing similar CPUs to their customers. They are also missing a price for some of the CPUs. Identify
the missing values, use imputation to replace the missing values and then a suitable clustering
algorithm to cluster the CPUs.
Your report has two objectives:
1. Show how you can use imputation to replace the missing values and then evaluate the
imputed values.
2. Utilise a suitable clustering algorithm to cluster the CPUs. Provide and explain the
information in a dendrogram.
Your (1,500 word maximum) report should use tables and figures as appropriate as well as text to
present your findings. No appendices are required, and any material provided in appendices will not
contribute to the final mark. This section will be marked using the following marking scheme:
LUBS5308M01
Success Criteria Weighting
General
Presentation
Use of tables and graphics