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MIS272 – Predictive Analytics – Trimester 2 2024
Summative Assessment Task 2 (Individual)
DUE DATE: Friday, 20 September 2024, by 8:00pm (Melbourne time)
PERCENTAGE OF FINAL GRADE: 40%
WORD COUNT: Maximum number of words: 1400
Description
Purpose
This task provides you with opportunities to understand and apply predictive analytics techniques in real-world situations (ULO2), as outlined below. By completing this task, you will demonstrate your specialised and integrated knowledge of business analytics (GLO1), your ability to evaluate complex business information to advance critical and analytical thinking and judgement (GLO4), and your ability to solve ill-defined real world problems, by drawing on your analytical skills to interpret and analyse business data to develop solutions (GLO5).
Context and Specific Requirements
You have been provided sample data (available on our unit site as part of the assessment resources for this assignment) regarding salary and benefits paid to a selection of employees. Each individual employee has been given an anonymous employee ID so they can be uniquely referred to in the data set. You are asked to explore and analyse the data set and develop AI Studio (RapidMiner) processes for the following tasks:
Task A: Explore various aspects of the data to gain insights on the employee data; e.g., in the past 5 years, which of the top 3 most popular jobs received the highest average Total Salary? Use appropriate visualisations to demonstrate your findings.
Task B: Find whether it is possible to accurately predict each employee’s Total Compensation from the values given in the other attributes in the data set (carefully consider your selection of attributes).
Explain how the predictive model could be used to estimate Total Compensation.
Task C: Find the Job Families that are frequently listed against same Unions.
You may check the original source website at https://data.sfgov.org/City-Management-and-Ethics/
Employee-Compensation/88g8-5mnd for any further information. The data set is governed by DataSF and you should read the Terms of Use of the data set at https://datasf.org/opendata/terms-of-use/. Your solutions in this assignment will be for educational purposes only.
Further instructions
• The dataset, report templates, and accompanying notes (A2 Notes) for this assignment are available on the unit site on CloudDeakin.
• You must use the provided template for your report. Your final report must adhere to page the page limits as only pages within the limits will be marked. It is essential that the executive summary section of your report is written for a non-technical reader (e.g., a senior manager at AirBnB) and that the remaining parts of the report are written for a technical reader (e.g., a business analyst or data scientist).
• You must only use AI Studio (RapidMiner) for your analytical process modelling. Your RapidMiner processes must be self-contained and adequately documented to enable replication by assessors.
• The consistency of your RapidMiner file(s) will be checked against the results in your report. You must not modify the data file provided for this assignment before importing it into RapidMiner.
Learning Outcomes
This task allows you to demonstrate your achievement towards the Unit Learning Outcomes (ULOs) which have been aligned to the Deakin Graduate Learning Outcomes (GLOs). Deakin GLOs describe the knowledge and capabilities graduates acquire and can demonstrate on completion of their course. This assessment task is an important tool in determining your achievement of the ULOs. If you do not demonstrate achievement of the ULOs you will not be successful in this unit. You are advised to familiarise yourself with these ULOs and GLOs as they will inform you on what you are expected to demonstrate for successful completion of this unit.
The learning outcomes that are aligned to this assessment task are:
|
Unit Learning Outcomes (ULOs) |
Graduate Learning Outcomes (GLOs) |
|
ULO2: Understand and apply predictive analytics techniques in real-world situations. |
GLO1: Discipline-specific knowledge and capabilities - Demonstrate a specialised and integrated understanding of contemporary body of knowledge of business analytics to research, design and implement projects with creativity and initiative. GLO4: Critical thinking - Evaluate complex business information using specialised and advanced critical and analytical thinking and judgment. GLO5: Problem solving - Use research skills and analytics techniques to interpret data, analyse business environments, and develop advanced solutions for authentic (real world and ill-defined) problems. |
Submission
You are required to submit partial submissions and your final submission of your report and RapidMiner process files.
You must submit your assignment in the Assignment Dropbox in the unit CloudDeakin site on or before the due date. No email submissions will be accepted.
The files and format for all submissions are:
• Your report according to the submission template as a PDF file.
• all AI Studio (RapidMiner) process files (in the RMP format) combined as a single ZIP file.
Submitting a hard copy of this assignment is not required. You must keep a backup copy of every assignment you submit until the marked assignment has been returned to you. In the unlikely event that one of your assignments is misplaced you will need to submit your backup copy.
Any work you submit may be checked by electronic or other means for the purposes of detecting collusion and/or plagiarism and for authenticating work.
When you submit an assignment through your CloudDeakin unit site, you will receive an email to your Deakin email address confirming that it has been submitted. You should check that you can see your assignment in the Submissions view of the Assignment Dropbox folder after upload and check for, and keep, the email receipt for the submission.
Marking and feedback
The marking rubric indicates the assessment criteria for this task. It is available in the CloudDeakin unit site in the Assessment folder, under Assessment Resources. Criteria act as a boundary around the task and help specify what assessors are looking for in your submission. The criteria are drawn from the ULOs and align with the GLOs. You should familiarise yourself with the assessment criteria before completing and submitting this task.
Students who submit their work by the due date will receive their marks and feedback on CloudDeakin 15 working days after the submission date.