QBUS3600 Individual Assignment 1 - Mad Paws
Due dates: Friday 29 March 2024
Value: 30%
Notes to Students
1. The assignment MUST be submitted electronically to Turnitin through QBUS3600
Canvas site. Please do NOT submit a zipped file.
2. The assignment is due at 5:00pm on Friday 29 March 2024. The late penalty for the
assignment is 5% of the assigned mark per day, starting after 5pm on the due date.
The closing date Friday 12 April 2024 is the last date on which an assessment will be
accepted for marking.
3. Your answers shall be provided as a word-processed report (Microsoft Word, LaTeX or
equivalent) giving full explanation and interpretation of any results you obtain.
Output without explanation will receive zero marks.
4. Be warned that plagiarism between individuals is always obvious to the markers of
the assignment and can be easily detected by Turnitin.
5. The dataset for this assignment can be downloaded from Canvas. The dataset is
highly confidential, and you have responsibility to keep it secure and for it to be used
only for your QBUS3600 coursework.
6. Presentation of the assignment is part of the assignment. Marks are assigned for
clarity of writing and presentation.
7. You should submit your Python code or Jupyter notebook to the separate submission
page available on Canvas. Marks will be deducted if the code fails to execute
properly.
8. You may insert small sections of your code into the report for better interpretation
when necessary. However, you must consider the audience of your report.
9. Think about the best and most structured way to present your work, summarise the
procedures implemented, support your results/findings and prove the originality of
your work.
10. Numbers with decimals should be reported to the second decimal point.
2023S2 QBUS3600 Assignment 1 - Mad Paws 1
Background
Mad Paws is an online marketplace that provides pet services from over 40,000 pet carers
across Australia. With Mad Paws, pet owners can search and connect with nearby pet sitters
who can help take care of their pet at times when the owner is unable to. Mad Paws offers a
variety of services ranging from pet sitting where the sitter either stays at the owner’s house
with the pet or the pet stays at the sitter’s house, dog walking, dog training, or even short
house visits where sitters can drop by the owner’s house to feed the pet.
The booking process first involves:
1. Searching for potential nearby sitters through the Mad Paws’ website or app. Owners
input their location, pet service that they are looking for, the number and type of
pets they have as well as the request date for the service.
2. Mad Paws will then present a list of nearby sitters. Sitters list their own prices,
provide their location and other useful information such as what type of pets they
are willing to work with (large dogs, small dogs, cats etc.), their type of house,
whether they have children and other pets etc.
3. Owners then contact the sitter that they have chosen after which the sitter approves,
resulting in a created booking.
4. The sitter will finally provide the service at the requested date and complete the
booking. The owner also has the option to cancel anytime prior to the completion of
the booking, resulting in an uncompleted booking. Alternatively, the sitter can
decline the booking request or not respond which results in an expired and also
uncompleted booking.
To understand this process more, you can visit the Mad Paws website or download the app
to search up pet sitters.
Mad Paws wishes to understand factors that drive booking completion between pet
owners and pet sitters. By better understanding these relationships, Mad Paws can provide
pet owners and their pets with a better experience by ranking and matching them with the
best sitters that are most suitable for their needs.
Task 1 – Preliminary Investigation (80 marks)
You have been given a dataset from Mad Paws which contains the following 5 tables:
● Training Reponse: ~59.3k rows for the training data where each row contains a pet
owner and sitter pair, the booking created date, service type, pet type and the
response (1 for completed booking and 0 for uncompleted booking).
● Test Response: ~16.4k rows for the testing data. The features provided are the same
as the Training Reponse table.
● Sitter Stats Basic: ~77.5k rows containing basic statistics for a sample of pet sitters
such as their completion rate, response rate, total reviews etc. The statistics also
have a corresponding timestamp in each row to indicate when the statistic was
calculated.
2023S2 QBUS3600 Assignment 1 - Mad Paws 2
● Owners Pet Detail: ~6.8k rows containing details of the pet owner and their pet such
as their birthday, pet breed, pet type etc.
● Booking Data: ~901k rows where each row is a unique booking between a pet owner
and sitter; provides information related to the time of booking, pet service
requested, booking status and pet details.
The dataset will become available after you have returned your signed Deed Poll to the
course coordinator.
As a business analyst, you will do a preliminary Exploratory Data Analysis (EDA) over the
dataset. You are expected to find or reveal all possible properties, characteristics, patterns,
and statistics hidden in the datasets. The results from your EDA may be used for the final
goal of identifying the top attributes that are likely to predict whether a booking request will
result in a completed booking. You may consider investigating other booking outcomes (e.g.
expired bookings, declined bookings etc.), but the focus is to determine which factors lead
to a booking request between owner and sitter to result in being accepted versus not
accepted.
Note that Mad Paws is already aware of some obvious factors (in the Sitter Stats Basic Table)
resulting in completed bookings such as sitter completion rates or number of bookings a
sitter has completed with an owner before. As such, they are particularly interested in
drivers of completed bookings that may not seem so obvious. Therefore, while you are still
encouraged to analyse these obvious statistics (as they may be useful features for increasing
model performance), please also make sure to analyse the less obvious factors in addition.
For example, one hypothesis you may consider is whether some owners match better with
sitters that focus on specific breeds etc? Also take care to avoid data leakage when using the
pre-computed statistics from the Sitter Stats Basic Table. You can use the timestamp
corresponding to each statistic to avoid including any future data.
Additionally, it's crucial to acknowledge that the dataset is organized by service type and
owner type. This distinction is vital for the analysis the Mad Paws team is interested in
conducting, which revolves around examining the variability in performance across different
service and pet categories. They are keen on testing the hypothesis that proficiency in one
service does not necessarily translate to competence in another. The same principle is
hypothesized to apply to the handling of different pet types.
Write a report, limited to 15 pages (including everything except for appendices), to describe,
explain, and justify your findings to the Mad Paws Management Team. Make sure your
report is concise and objective.
List key resources as references in the end of your report, such as journal articles,
conference papers, reports, news and software etc. Use APA style for your references.
Task 2 – Executive Briefing (20 marks)
2023S2 QBUS3600 Assignment 1 - Mad Paws 3
You have been asked to summarise your findings so that they can be shared with the wider
business and in particular, management. This one-page briefing should concisely describe
your findings to a non-technical audience and primarily address the business problem. In the
briefing you should also outline your suggestions for acting on your findings.
You are limited to a maximum of 1 page (included in the overall 15 pages).
Marking and Key Rules
Your reports will be marked against the following principles:
• Demonstrate a clear understanding of the problem
• Demonstrate consideration for the audience
• Clear outline and demonstration of investigation process
• Use of relevant statistical tests
• Clear explanation of outputs. Proper justification of used methods.
• The overall analysis is sound and logical
• Clearly draw conclusions based on analysis
• Statements are clear, concise and accurate, with correct spelling, free of grammar
errors and correct use of punctuation
• Use of visual presentation is appropriate
• The report is well structured, and sentences are well connected
• Closely follow a referencing style specified in Business School Referencing Guide (e.g.
APA) with consistency
• Clear, concise and commented Python code, if any.
A formal marking rubric is uploaded to canvas.
Datasets and Additional information
You have been provided a dataset in CSV format.
Mad Paws has made an effort to ensure the data is relatively clean, however, we encourage
you to perform their checks and conduct the necessary data processing and feature
engineering as required.
2023S2 QBUS3600 Assignment 1 - Mad Paws 4