COMM1190 Assessment 2: Team Report
Individual Component: Due Week 7 3:30 pm Monday (AEDT) (10 marks)
Team Component: Due Week 8 3:30 pm Monday (AEDT) (20 marks)
30%
A written report
Individual Component: 2-page limit excluding references and appendix.
Team Component: 3-page limit excluding references and appendix.
Via Turnitin on Moodle course site
Brief
$XVWUDOLD¶V*OREH7URWWHUVD WUDYHOERRNLQJFRPSDQ\ WKDW UH-sells international and
domestic flights, recently conducted a survey to gauge consumer satisfaction with their
website. Intrigued by the internal memo, the Customer Insights team manager has
asked you and several other analysts to work together to understand what is driving
customer website satisfaction and what actions the Customer Insights Unit should
take.
Since the data was collected in 5 waves, the manager has asked that each team
member prepare their own individual 2-page technical report on one segment of the
data to determine what they think drives customer website satisfaction using a model
of the survey and website data.
Next, the Manager wants the team to choose one model to explain website satisfaction
and make appropriate conclusions and recommendations for the next steps. The
recommendation should be presented in a one-page executive summary, providing
context to the scenario and analysis. The Customer Insights team manager will provide
this short report to senior management. To ensure credibility and reproducibility, the
manager requires the entire analysis to be conducted in R and has asked your team
to prepare a two-page report summarising the rationale and strategies for selecting
the chosen model. This technical report will be internal to the Customer Insights team.
To provide richer insights, the manager has asked IT support to provide additional data
to each team member. IT support provided data on whether each unique customer
who completed the survey has since returned to the website. They also linked
customers with Google reviews and provided a column indicating if the review had a
positive or negative sentiment and whether the Google review mentioned anything
about the website. 7KHPDQDJHULVXQVXUHDERXWWKHH[WUDGDWDSRLQWV¶KHOSIXOQHVV
Task
Using R, you will explore a dataset and use predictive modelling to address the
PDQDJHU¶VTXHULHVYou will have to undertake the following individual and team tasks.
Individual Report:
x Present a predictive model explaining website satisfaction.
x Describe other candidate models you considered but did not select as your
preferred model.
x Explain your rationale and strategy for selecting your preferred model.
x Clearly, concisely and professionally communicate your results and analysis for a
more technical audience.
x There is a two-page limit (You do not need to provide general context to the
problem).
x Submit your R-code as an Appendix to this document.
x Each team member must work with a different segment of the data.
Team Report:
x Present a predictive model explaining website satisfaction.
x Explain the synthesis processes of 1) model selection, which should be rooted in
the models submitted by individual team members, and 2) how your analysis
support the findings, conclusions, and recommendations.
x Clearly, concisely and professionally communicate the context, findings, and
recommendations for a managerial non-technical audience in a 1-page executive
summary.
x Clearly, concisely and professionally communicate the chosen model, model
selection process, and any relevant results and analysis for a more technical
audience in a 2-page report.
x Submit all relevant team-based R-codes as an Appendix to this document.
Guidance on Data Analysis:
x Critically and collaboratively, reflect on each team member's feedback from
assessment 1 and use it to develop your team project where applicable.
x Use descriptive analytics to identify the key factors impacting DXVHU¶VDSS
satisfaction. Descriptive Analytics refers to statistics and visualisation techniques.
For example, a box plot and a bar chart are different techniques.
x 8VHSUHGLFWLYHDQDO\WLFVWRGLDJQRVHDQGRUIRUHFDVWIDFWRUVWKDWLQIOXHQFHXVHUV¶
app satisfaction. Predictive Analytics refers to linear regression and regression
trees modelling techniques. You should use the modelling techniques discussed
in lectures and workshops (i.e., do not use modelling techniques beyond the
scope of this course).
x For each modelling technique (e.g., linear regression, decision tree, etc.) you use,
consider trying several models using different independent variables to predict the
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to be tKH³EHVW´RXWRI\RXUFDQGLGDWHPRGHOV\RXFDQDVVHVVLWEDVHGRQits
goodness of fit and performance in predicting the outcome variable.
x Importantly, ensure that your predictors make sense and provide evidence that
your conclusions are insensitive to the precise model presented.
x If your core conclusions change with variations in appropriate models, then try to
explore the data more to understand the differences.
x Only use methods and criteria learned from this course to evaluate performance.
x Develop coherent logic from your business issue identification to your variables
and modelling techniques selection and your recommendations.
x Explicitly state any key assumptions that impact your data analysis.
x Note: the dataset and the data dictionary will be provided separately.
Requirements and Mark Breakdown:
Criteria Description Ind. Grp. Total
Problem Analysis Apply rigorous analysis, appropriate
frameworks, tools, and standards to
develop and/or evaluate data and
models.
8 10 18
(60%)
Quality of
Conclusions and
Recommendations
Develop well-reasoned, appropriate
conclusions and recommendations
supported by the data and analysis.
0 6 6
(20%)
Communication
and organisation
The report is professionally presented,
using language to convey ideas and
information effectively and accurately.
2 4 6
(20%)
Submission Instructions
Individual Component (10 Marks)
This document, to be completed individually, is due Monday, Week 7. We suggest you
finish this task earlier to provide more time for the collaborative component.
If you do not submit a credible attempt for the individual component by the Monday Week
7 deadline, you will not receive marks for the team component.
Team Component (20 Marks)
This document, to be completed as a team, is due Monday, Week 8. We suggest you
do not approach the task using divide and conquer approaches. Instead, work
collaboratively on each section of the reports.
The team lead or a designated team member needs to submit the written report with all
required information via the Turnitin submission link on Moodle. Note that only one report
from a group is required.
Your submission must be in a Word or PDF format, accompanied by a cover sheet (to be
provided on Moodle). Please note that you must nominate a team lead on the cover sheet
by specifying their name and zID.
The appendix must have all relevant R codes. The codes should take the raw data file
provided as the input and must be able to reproduce all analyses in the team report.
5% of the marks available for the assessment will be deducted for this assessment if you
do not submit a fully completed and signed cover page.
should be delivered at a professional standard. If problems emerge in your group, then
these problems should, in the first instance, openly be discussed in the group (different
members might have different views), and resolutions should be agreed on. If internal
arrangements repeatedly fail to remedy the situation, then you should bring the issues to
the attention of the LIC.
The LIC/ACC may call a group meeting in which each group member will be asked to
describe their input into the assignment and provide supporting documentation of this
effort using meeting minutes/notes and emails.
Note: non-university platforms such as Meta/Facebook messages, texts, Whatsapp, etc.
will not be considered. If group members are found to be making an inadequate effort or
delivering poor quality, they will be counselled to improve their effort. If sufficient
improvement is not made despite group efforts and LIC interventions, the mark of
underperforming group member(s) may be moderated to reflect the relatively lower input
into the assignment.
Unequal Contribution
After submitting the assessment. There will be a 72-hour period where any team member
can submit a form to report unequal contributions, which can lead to adjusting of marks.
Unequal contributions must be supported by evidence documenting WHDP PHPEHUV¶
efforts and contributions using meeting notes and emails. Again, non-university platforms
such as Facebook messages, texts, and WhatsApp messages will not be considered. If
there are reports of inconsistent efforts in the teamwork component, the quality of this
individual submission may also be considered as evidence.
7KHWHDP¶VJRDOLVWREHFROODERUDWLYHDQGSUHYHQWXQHTXDOFRQWULEXWLRQ6RLIDQ\LVVXHV
emerge, they must be flagged with the teaching team as early as possible to allow for
support in achieving collaborative outcomes. If you are concerned about unequal
contribution, your group should develop and record a project management plan, specifying
key milestones and each team mHPEHU¶VUHVSRQVLELOLWLHV
Groups Rules
You must form a group of 3 or 4 people with peers from your tutorial section. There is hard
maximum of 4 people per group. Once you have your group, please inform your tutor.
Marking Rubric for Team Assessment
Criteria High Distinction (85%-100%)
Distinction
(75%-84%)
Credit
(65%-74%)
Pass
(50%-64%)
No Bueno
(0%-49%)
Individual and Team
Problem Analysis
(60%)
Demonstrates a thorough
understanding of the
business problem or issue,
identifies relevant
questions and uses
appropriate frameworks,
tools, and standards to
develop and evaluate data.
Explicitly presents a
coherent and clear logic
between business issues,
analytical techniques, and
variable selection.
The justification is sound
and convincing. Skillfully
explores data with
compelling explanations of
the issues identified.
Demonstrates a good
understanding of the
business problem or issue,
identifies relevant
questions, and applies
appropriate frameworks,
tools, and standards to
develop and evaluate data.
Explicitly presents a
coherent and clear logic
between business issues,
analytical techniques, and
variable selection.
The justification is
convincing. Explores data
with explanations of the
issues identified.
Demonstrates a
satisfactory understanding
of the business problem or
issue, identifies some
relevant questions, and
uses some appropriate
frameworks, tools, and
standards to develop and
evaluate data. Presents a
somewhat coherent and
clear logic between
business issues, analytical
techniques, and variable
selection.
The justification is partially
convincing. Explores data
adequately with adequate
explanations of the issues
identified.
Demonstrates a limited
understanding of the
business problem or issue,
does not identify relevant
questions, and does not
use appropriate
frameworks, tools, and
standards to develop and
evaluate data. Does not
present a coherent and
clear logic between
business issues, analytical
techniques, and variable
selection.
The justification is not
convincing. Explores data
inadequately with
insufficient explanations of
the issues identified.
Does not demonstrate a
basic understanding of the
business problem or issue,
does not identify relevant
questions, and does not
use appropriate
frameworks, tools, and
standards to develop and
evaluate data. Does not
present any coherent or
clear logic between
business issues, analytical
techniques, and variable
selection.
The justification is absent.
Does not explore data
adequately with insufficient
explanations of the issues
identified.
Individual and Team
Communication and
Organisation (20%)
Uses language effectively
and accurately to convey
ideas and information, with
clear and concise writing
that is well-structured and
free of errors.
The tables and graphs are
presented professionally.
The team report reads
cohesively, with consistent
writing style and logical
flows.
Uses language effectively
and accurately to convey
ideas and information, with
clear writing that is well-
structured and mostly free
of errors.
The tables and graphs are
mostly presented
professionally.
The team report mostly
reads cohesively, with
consistent writing style and
logical flows.
Uses language somewhat
effectively and accurately
to convey ideas and
information, but the writing
may lack clarity, structure,
or contain errors.
The tables and graphs are
somewhat professional.
The team report reads
somewhat cohesively in
terms of writing style and
logical flows.
Uses language ineffectively
or inaccurately to convey
ideas and information, with
unclear or poorly-structured
writing that contains errors.
The tables and graphs are
largely unprofessional.
The team report is largely
incohesive in terms of
writing style and logical
flows.
Uses language
incoherently or inaccurately
to convey ideas and
information, with writing
that is unclear, poorly-
structured, and contains
numerous errors.
The tables and graphs are
all unprofessional.
The team report is entirely
incohesive in terms of
writing style and logical
flows.
Criteria High Distinction (85%-100%)
Distinction
(75%-84%)
Credit
(65%-74%)
Pass
(50%-64%)
No Bueno
(0%-49%)
Quality of
Conclusions and
Recommendations
(20%)
Develops well-reasoned,
appropriate conclusions or
solutions based on the
results of the analysis. The
results of each analytic
technique performance and
findings are correctly
interpreted and critically
examined supported by
academic references when
appropriate.
Results interpretation is
relevant and meaningful in
the case context.
Develops good conclusions
or solutions based on the
results of the analysis. The
results of each analytic
technique performance and
findings are correctly
interpreted and examined.
Results interpretation is
generally relevant and
meaningful in the case
context.
Develops satisfactory
conclusions or solutions
based on the results of the
analysis. The results of
each analytic technique
performance and findings
are partially interpreted and
examined.
Results interpretation is
somewhat relevant and
meaningful in the case
context.
Develops limited
conclusions or solutions
based on the results of the
analysis. The results of
each analytic technique
performance and findings
are not interpreted and
examined.
Results interpretation is not
relevant or meaningful in
the case context.
Develops no conclusions or
solutions based on the
results of the analysis. The
results of each analytic
technique performance and
findings are not interpreted
and examined.
Results interpretation is not
relevant or meaningful in
the case context.