HND Computing: Business Analytics Report on Automobile Data

This coursework report presents a comprehensive business analytics analysis of the automobile industry, focusing on a dataset from the American Statistical Association Exposition in 1983. The report begins with an explanation of the analysis's expectations and benefits for the automobile industry. It details the tools, techniques, and methodologies employed, including statistical software for data analysis. The analysis includes finding descriptive statistics (minimum, maximum, mean, median, mode) for horsepower, summary statistics for horsepower, weight, and displacement, and graphical representations of these variables. Central tendency analysis, including standard deviation and bell curves, is performed. The report also conducts hypothetical mean and variance testing to compare horsepower across different nations and employs statistical hypothesis testing to examine the relationships between horsepower and weight, horsepower and engine displacement, and horsepower and the number of cylinders. Normality testing is incorporated in the hypothesis testing. The report concludes with findings from the data analysis, including recommendations for the automobile industry, and may include regression analysis findings.

Assignment Cover Sheet
Qualification Module Number and Title
Higher National Diploma in Computing &
Software Engineering
COM5221 - Business Analytics
Student Name & No. Assessor
Chanidu Heshan Perera
CL/HNDCSE/88/03
Chanuka Dombagahawatta
Hand out date Submission Date
2020/7/21 2020/8/30
Assessment type
Coursework
Duration/Length of
Assessment Type
3 weeks
Weighting of Assessment
100 %
Learner declaration
I, ………………………………………….<name of the student and registration number>,
certify that the work submitted for this assignment is my own and research sources are fully
acknowledged.
Marks Awarded
First assessor
IV marks
Agreed grade
Signature of the assessor Date
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FEEDBACK FORM
INTERNATIONAL COLLEGE OF BUSINESS & TECHNOLOGY
Module:
Student:
Assessor:
Assignment:
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Strong features of your work:
Areas for improvement:

Acknowledgement
I would like to convey my special thanks of gratitude my lecturer, Mr. Chanuka Dombagahawatta
who guided me throughout this research project. Without his valuable guidance, this project
would not have been successful one. Further, I would also like to thank our institute for having
high quality library facilities with suitable guidebooks suit our needs of completing the project.
At last, I would also like to thank my parents and friends who helped a lot to finalizing this
assignment within a short time period.
Thank you.
Chanidu Heshan–03,
HND Batch 88
Course work
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Marks Awarded:

Coursework
Learning outcomes covered
 Understand Business Analytics methodologies, tools and the techniques
 Evaluate business advantages produced by business analytics.
 Be able to perform a business analysis
 Be able to propose solution for a business problem or creating opportunity using
appropriate business analytics methodologies, tools and the techniques
Scenario and the Task
Introduction
The Business Analytics subject domain is considered to be one of the major area
where most of the companies and various profitable and non- profitable institutions consider for
achieving the best decision support in their respective various operations life cycles. Because of
the economy is growing rapidly to achieve tangible and intangible as well as financial and non-
financial targets all most all the government and private organizations required to consider
precision and accuracy of their management decisions in all major three levels; operational,
tactical and strategic. The amount of information generated in modern agile economic
environment is very high and nature of consistency also highly varies within short time frame.
Because of the fact that utilization of big data analysis considered as one of the prime concern to
deal with the data to produce credible and valuable information. During the process of
conversion data to decision supportive information it is very important use different data analysis
methods, techniques and tools that are comprehensively explained in data analytics. The high
importance of data analytics subject elements leads to include those in modern management
information systems and decision support information systems for enabling online analytical
processing to incorporate with connected operational databases, data marts and data warehouses.
In performing big data analysis, it is very important to use good statistical software. At present
there are many such products available under generic or bespoke software category considering
open source or closed source. Usually open source products are financially feasible for many
organizations compared to closed source products. At present big data analysis rapid growth
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identifiable in open source category with frequent versions and many feature extensions
compared to closed source. On the other hand, side much reliable many software products have
been released by industry pioneer solution providers. Therefore, section of the best product for
data analysis is also need to be done wisely by relevant authorities of organizations for their
objectives to be precisely achieved.
SCENARIO
The automobile industry considered as one of the major contributing industries for world’s
economic and technology development. Specially American, German, European and Japanese
companies pioneered for the automobile revolution of the world by introducing innovative
engineering technologies and methodologies for automobile manufacturing.
Manufacturing durable, hard & expensive vehicles was the practice initially but gradually
changed it to more comfortable, safe, high-speed and affordable vehicle manufacturing.
The dataset comprises of information about various types of automobiles manufactured by
Americans, Europeans and Japanese companies. The information includes vehicle’s Engine
displacement, cylinders, horsepower, weight, acceleration, year, origin and name. Based on the
information available it is feasible for understand performance variations and associations of
motor vehicles depending on the nature of engine, transmission subsystem, fuel subsystem,
electrical subsystems, breaking subsystem, passenger subsystem and climate control subsystem.
Any changes in those directly influence to have performance variations in the motor vehicle.
As a data analyst of newly opening automobile manufacturing company in Sri Lanka you are
required to prepare a report comprises of findings of the data analysis based on the dataset
associated with this.
Survey Data Dictionary
Variable name Description
mpg miles per gallon
cylinders Number of cylinders between 4 and 8
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The original dataset has been provided to you as a separate data file labeled “Auto.csv” which
was used by American Statistical Association Exposition in 1983.

displacement Engine displacement (cu. inches)
horsepower Engine horsepower
weight Vehicle weight (lbs.)
acceleration Time to accelerate from 0 to 60 mph (sec.)
year Model year (modulo 100)
origin Origin of car (1. American, 2. European,
3. Japanese)
name Vehicle name
Tasks
1. Provide an in detailed explanation about the expectation of the analysis and benefits generated
for the automobile industry.
(5Marks)
2. Explain tools, techniques and methodologies going to use for the analysis.
(6Marks)
3. Find out minimum, maximum, mean, median, mode of horsepower of the vehicles. (6 Marks)
4. Find out summary statistics of horsepower, weight and displacement of the vehicles. (6
Marks)
5. Graphically represent horsepower, weight and engine displacement of vehicle models during
the mentioned period of the survey. (10 marks)
6. Conduct central tendency analysis for horsepower, weight and engine displacement and find
out standard deviation of those. Represent finding graphically using bell curves. (12 Marks)
7. Using most suitable statistical hypothetical mean and variance testing justify whether what
nations manufactured differentiated horsepower oriented motor vehicles. (10 Marks)
8. Using statistical hypothetical testing prove, whether there is a statistically significant
relationship exist with horsepower and weight in vehicle models. (10 marks)
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9. Using statistical hypothetical testing prove, whether there is a statistically significant
relationship exist with horsepower and engine displacement in vehicle models. (10 marks)
10. Using statistical hypothetical testing prove, whether there is a statistically significant
relationship exist with horsepower and number of cylinders in the engine in vehicle models.
(10 Marks)
11. Write a conclusion based on the findings of the data analysis based on above findings and
suggest necessary recommendations. (15 Marks)
 Question no 8,9 and 10 should be incorporated with normality testing
 Note: The conclusion can include the findings of suitable regression analysis as well.
Marking Scheme
Task-1 contains 5 marks
Criteria
Marks
Out of 5
Fail
Not Explained the scenario and not included the benefits provided
by the analysis for the selected company/institution etc.. 0-1
Pass
Explained the scenario. 1-2
Good
Explained the benefits provided by the analysis for the selected
company/institution etc. 2-3
Excellent
Well explained the scenario and the benefits provided by the
analysis for the selected company/institution. 3-5
Task-2 contains 6 marks
Marks
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Criteria Out of 6
Fail
Not Stated tools, techniques and methodologies going to be used
for analysis
0-1
Pass
Stated tools, techniques and methodologies going to be used for
analysis
1-2
Good
Stated tools, techniques and methodologies going to be used for
analysis. Explained the mentioned tools, techniques and
methodologies.
2-4
Excellent
Stated tools, techniques and methodologies going to be used for
analysis. Well explained the mentioned tools, techniques and
methodologies.
4-6
Task-3 contains 6 marks
Criteria
Marks
Out of 6
Fail
Not used minimum, maximum, mean, median, mode functions to
get respective statistics of provided data 0-2
Pass
Used minimum, maximum, mean, median, mode functions to get
respective statistics of provided data
2-4
Good
Used minimum, maximum, mean, median, mode functions to get
respective statistics of provided data and got an accurate set of
results and explained briefly about what obtained.
4-5
Excellent
Used minimum, maximum, mean, median, mode functions to get
respective statistics of provided data and got an accurate set of
results and well explained about what obtained.
5-6
Task-4 contains 6 marks
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Criteria
Marks
Out of 6
Fail
Not included summery statistical data using summary statistical
function. 0
Pass
Included summery statistical data using summary statistical
function.
6
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Task-5 contains 6 marks
Criteria
Marks
Out of 10
Fail
Not Included bar chart/pie chart/ to represent data provided
graphically. 0-1
Pass
Included bar chart/pie chart/ to represent data provided
graphically.
1-4
Good
Included bar chart/pie chart/ to represent data provided graphically
and included brief information about what is represented in the
charts.
4-7
Excellent
Included bar chart/pie chart/ to represent data provided graphically
and included well described information about what is represented
in the charts.
7-10
Task-6 contains 12 marks
Criteria
Marks
Out of 12
Fail
Not Included bell curves based on data provided 0-1
Pass
Included bell curves based on data provided 1-6
Good
Included bell curves based on data provided and
Described information represented in the charts briefly 6-10
Excellent
Included bell curves based on data provided and
Well described information represented in the charts briefly
10-12
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Task-7 contains 10 marks
Criteria
Marks
Out of 10
Fail
Not Inclusion of hypothetical statement considering null
hypothesis and alternative hypothesis 0-1
Pass
Inclusion of hypothetical statement considering null hypothesis
and alternative hypothesis and statistical justification of result
based on mean and variance analysis test. Yet some errors exists.
1-5
Good
Inclusion of hypothetical statement considering null hypothesis
and alternative hypothesis. Good statistical justification of result
based on mean and variance analysis test.
6-7
Excellent
Inclusion of hypothetical statement considering null hypothesis
and alternative hypothesis. Excellent statistical justification of
result based on mean and variance analysis test.
7-10
Task-8 contains 10 marks
Criteria
Marks
Out of 10
Fail
Not Inclusion of hypothetical statement considering null
hypothesis and alternative hypothesis 0-1
Pass
Inclusion of hypothetical statement considering null hypothesis
and alternative hypothesis and statistical justification of result
based on correlation analysis test
1-5
Good
Inclusion of hypothetical statement considering null hypothesis
and alternative hypothesis and statistical justification of result
based on correlation analysis test supported by normality test
6-7
Excellent
Inclusion of hypothetical statement considering null hypothesis 7-10
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