COM5021 Data Analysis and Visualisation Assignment Brief | AU

Published: 23 May, 2025
Category Assignment Subject Computer Science
University Arden University Module Title COM5021 Data Analysis and Visualisation

Data Analytics and Visualisation Assignment

As part of the formal assessment for the programme you are required to submit a Data Analytics and Visualisation assignment.

Please refer to your Student Handbook for full details of the programme assessment scheme and general information on preparing and submitting assignments.

Module description: Coursework 100%

Description: The assignment is given as three tasks, each one building from the previous within one dataset. Each task is to be answered individually, unless multiple components have been given. Task 1 has been designed to check your importing, data cleaning and integrity processes. Task 2 continues to build upon Task 1 and validates your knowledge and understanding of descriptive statistics and hypothesis testing, the bedrock of any data analysis. Finally, Task 3 allows you to demonstrate your dashboard configuration and analytical skills. Below are the measures and attribute information for the associated dataset, which will be given to you.

Attribute Information

Attribute Measure Description
Sex Male (M), Female (F), Combined Infancies (I)  
Length mm Longest Shell Measurement
Diameter mm Perpendicular to Length
Height mm With Meat in Shell
Whole Weight grams Weight of Whole Abalone
Shucked Weight grams Weight of Meat
Viscera Weight grams Gut Weight
Shell Weight grams After being Dried
Age   Age in Years

A clear, concise analysis and application for all Tasks are to be given within the submission, complemented with screenshot evidence of all processes and results. You are to submit a single Word document for all three tasks and a single Excel workbook containing multiple worksheets, one worksheet for each task. Your student ID number must be clearly defined upon each uploaded file.

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COM5021 Learning Outcomes:

Coursework LO
Understand the different types of data and how to process, summarise and present it in a concise and meaningful way, acknowledging issues of data confidentiality and integrity. LO 1
Use appropriate IT packages to store, process and manipulate data. LO 2
Propose actions that are appropriate to the conclusions drawn from the data. LO 3
Effective Communication: Communicate effectively both verbally and in writing, using a range of media widely used in relevant professional contexts. Be IT, digitally and information literate. Graduate Attribute

Guidance

Your assignment should include: a title page containing your student number, the module name, the submission deadline and the exact word count of your submitted document; the appendices, if relevant; and a reference list in (see referencing section for more information). You should address all the elements of the assignment task listed below. Please note that tutors will use the assessment criteria set out below in assessing your work.

You must not include your name in your submission because Arden University operates anonymous marking, which means that markers should not be aware of the identity of the student. However, please do not forget to include your STU number.

Maximum word count: 4000 words

Please refer to the full word count policy, which can be found in the Student Policies section here: Arden University | Regulatory Framework

The word count includes everything in the main body of the assessment (including in-text citations and references). The word count excludes numerical data in tables, figures, diagrams, footnotes, reference list and appendices. All other printed words ARE included in the word count.

Students who exceed the word count by up to a 10% margin will not be penalised. Students should note that no marks will be assigned to work exceeding the specified limit once the maximum assessment size limit has been reached.

Assignment Task

Task 1 – Report

Details of Task 1

Importing and cleaning data

As part of a global Marine Biology company, you have been asked by the Head of Research to import and analyse this year’s collected Abalone Community data set, entitled abalone_data_2731.txt, using Excel. A description of the data set can be found in abalone_description_2731.txt. Before any analysis can be carried out, appropriate Excel processes to pre-process the data must be undertaken. Therefore, conduct all appropriate data pre-processing to enable you to conduct future accurate analysis. Once this has been completed, apply appropriate security processes on your worksheet to protect it before any analysis can be performed. For each pre-processing activity, the screenshot is required of the steps taken to achieve the cleaned data set in Excel.

(30 marks) (LOs: 1)

Task 2 – Hypothesis Testing

Details of Task 2

Having prepared the dataset in Task 1, perform an initial descriptive analysis study, with Histograms, so initial comparisons can be made between sexes. Finally, conduct an Inferential Hypothesis test, with appropriate null and alternative hypotheses on whether the Abalone gender has a significant impact on the entire weight. Once the appropriate hypothesis test has been concluded, write a summary of your statistical findings. For each activity detailed above, screenshot evidence is required of the steps taken to achieve each process in Excel and the result.

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(30 marks) (LOs: 3)

Task 3 – Dashboards

Details of Task 3

With tasks 1 & 2 now complete, create a fully interactive Dashboard in Excel, with slicers. Within the Dashboard, there will be three separate charts, which include two Pivot Charts for Length and Diameter. The third Pivot Chart is a chart of your choice, to add validity to your dashboard, relating to size equality between male, and female, plus combined infant Abalones.

With the aid of slicers, infer whether there is indeed disparity between male, female and combined infancy sizes and detail what Abalone, on average, is the smallest and largest. Plus, which sex lives the longest? Give justification for the design of the Dashboard, analysis and results. For each activity detailed above, screenshot evidence is required of the steps taken to achieve each process in Excel and the result.

(40 marks) (LOs: 2)

A clear, concise analysis and application for all Tasks are to be given within the submission, complemented with screenshot evidence of all processes and results. You are to submit a single Word document for all three tasks and a single Excel workbook containing multiple worksheets, one worksheet for each task. Your student ID number must be clearly defined upon each uploaded file.

As technology and platforms may change, your module tutor will provide you with up-to-date details.

Formative Feedback

You have the opportunity to submit an assignment for feedback once, and it is 30% of your entire submission. You, the student, are to choose 30%, not the tutor. to receive formative feedback.

The feedback is designed to help you develop areas of your work, and it helps you develop your skills as an independent learner.

If you are a distance learning student, you should submit your work by email. The last day for guaranteed feedback hand-in is Monday of week 9 at 23:58. If you are a blended learning student, your tutor will give you a deadline for formative feedback and further details.

Formative feedback will not be given to work submitted after the above date or the date specified by your tutor, if a blended learning student.

 

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