COMM1110 Evidence-Based Problem Solving
Assessment 4: Case project part 2
Guideline and Marking Rubric
Due date: Week 11: 11:59 AM (midday), Wednesday 24th April
Project Overview
In Assessment 3, you worked as a consultant, and your client, GreenMart, a retail
supermarket chain, needed assistance with a notable rise in food waste, especially in the
fresh food section. You employed techniques like the 2W and logic tree to organize
information and develop logical problem-solving strategies. Additionally, you conducted
basic Excel data analysis and initiated an ethical analysis of the dilemma.
Now, in Assessment 4, we'll conduct a more in-depth analysis to address the increased
food waste issue at GreenMart. This assessment mirrors the case project we encounter
daily as managers in the workplace. Therefore, we'll apply all the knowledge we've gained
in our course to help you develop statistical, ethics, and analytical skills necessary to solve
the problem.
You will use the same personal Excel data you downloaded from Assessment 3, and
we will continue to conduct data analysis based on that. If you need assistance, you
can refer to page 6 in the Assessment 3 Guideline document for instructions on how
to download your personal Excel data.
• Word Limit: 2,000 words with a 10% buffer, allowing for a maximum of 2,200 words without
penalty. There's no minimum word requirement, so any word count below 2,200 is acceptable.
• The word count rule is straightforward – everything in your report, such as headings,
subheadings, and in-text citations, contribute to the word count, except for the reference list
(bibliography), and any inserted screenshots or images. Use your Word document's built-in
word count feature to check your word count accurately.
• Structure and Format: No need to have cover page, introduction, or executive summary. Simply
begin your report directly with section 1. Write in a business report style (e.g., using an essay
format, formal language, headings, and subheadings to make your report easy to read).
• Referencing Style: While referencing is optional, if you choose to cite external information,
adhere to the Harvard referencing style for any sources cited in your report. (see the guideline
link - How to Cite Different Sources with Harvard Referencing | UNSW Australia)
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Section 1 – Further Statistical Excel Data Analysis (40%):
This section is approximately 700 words (guide only, not a word limit).
Apply all statistical data analysis skills you learned in our course to conduct a deeper analysis
of the food waste issue, using the same personal data file from Assessment 3.
1) Formulating Hypotheses on Variable Relationships:
Let's review your personal Excel dataset and the analysis you conducted on Food waste in your
Assessment 3. Based on that, you need to identify 3 or 4 variables you believe will influence
Quantity Wasted. Explain why you think they have an impact, and predict the strength (weak,
moderate, strong) and direction (positive or negative) of each relationship. No Excel data
analysis needed; just provide clear explanations.
Instruction - These variables you select aren't confined to the data in your Excel file; they can
be anything you deem fit and relevant, such as the inflation rate.
Next, drawing from what you learned in week 7, you need to develop a Null Hypothesis and
Alternative Hypothesis. Clearly state each and explain why you're creating them and how testing
them could help address the food waste issue. No specific Excel data analysis is required;
simply outline the hypotheses you want to create.
2) Correlation Analysis:
a) Shelf Time and Food Waste: Analyse the correlation between Shelf Time and Food Waste for
fruits and vegetables separately, using a suitable visualization tool such as a Table, Line Chart,
etc., to display the correlation in your report. Clearly explain the direction and strength of the
correlation and discuss how shelf time influences food waste.
b) Price and Food Waste: Analyse the correlation between Price and Food Waste for fruits and
vegetables separately, using a suitable visualization tool such as a Table, Line Chart, etc., to
display the correlation in your report. Clearly explain the direction and strength of the correlation
and discuss how shelf time influences food waste.
c) Exploring Other Factors: Explore 1 or 2 additional factors correlated with Quantity Wasted.
You can select any existing column in your Excel file or create new columns containing relevant
information based on existing data in your Excel. For each of these additional factors, analyse
the correlation between them and Food Waste for fruits and vegetables separately, using a
suitable visual tool such as a Table, Line Chart, etc., to display the correlation in your report.
Clearly explain the direction and strength of the correlation and discuss any insights these
additional factors provide into Green Mart’s food waste.
3) Regression Analysis
a) Selecting Variables for Regression Analysis: Before conducting the linear regression, you
need to select suitable variables you will include in your model. Please reflect on the hypotheses
you created in part (1) above and any insights you gained from the correlation analysis above.
Have your initial hypotheses changed based on the correlation results? Are there any new
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variables that should be included in the linear regression analysis? Provide a clear and concise
justification for each variable you want to add to your regression model, explaining its relevance
and potential contribution to addressing the Quantity Wasted issue.
b) Regression Analysis: Conduct a linear regression analysis to analyse the relationship
between Quantity Wasted and all variables your selected. Clearly explain how adding or
removing these variables affects your regression model outcomes. Interpret your model result,
considering their alignment with your initial hypotheses and correlation insights. Discuss the
implications for GreenMart's food waste and explain the most influential variable identified by
the regression model. You need to include screenshots of the key parts of your regression
model in the report, accompanied by your explanation of the findings.
Section 2 – In-depth Ethical Analysis on Ethical Dilemma (25%)
This section is approximately 600 words (guide only, not a word limit).
Apply the 7-step ethical decision-making framework (from Week 4’s lecture and tutorial) to
address one of the following ethical dilemmas:
a) Should GreenMart switch to smaller packaging, like 1 kg per package, or opt for larger
packaging, considering potential contributions to plastic pollution and consumer
preferences?
b) Should GreenMart invest in enhancing its supply chain logistics, such as improving
transportation efficiency and reducing delivery times, to mitigate food waste, even though it
might lead to increased product prices for consumers and higher fuel consumption resulting
in more carbon emissions?
Instruction: GreenMart is the main stakeholder here. Provide a clear explanation for each step,
and ensure you make your key points in each step clear. This model serves as one common
tool to guide your approach when dealing with an ethical dilemma issue during your internship.
Section 3 – Analytical Problem-Solving for Developing Solutions (35%):
This section is approximately 700 words (guide only, not a word limit).
1) Structuring the Argument:
GreenMart wants to understand how you structure your arguments to develop practical
problem-solving solutions. Please insert the provided table below directly into your report to
answer this question. All content within this table contributes to the word count, so ensure your
responses are concise and clear to read and avoid using screenshot.
Organize my arguments to develop practical solution
Situation ……..
Observation ………
Resolution ……..
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Instruction:
For Situation – Identify and summarize the current situation regarding the food waste issue,
explaining it to provide any reader who may read your business report with a clear
understanding of the report's purpose and context.
For Observations: Highlight key insights from your business analysis work, including insights
from your logic tree in Assessment 3, all Excel data analysis you have done from both
Assessment 3 and 4, and ethical considerations discussed in this report.
For Resolution, the key is to provide well-reasoned general directions, supported by all analysis
you conducted in this assessment, to address the food waste issue. These directions should
not be overly specific, as you will offer detailed recommendations in part (2) below.
2) Solution Recommendations:
Based on the argument structure you outlined in (1) above, you now need to present your
final recommendations and solutions on how GreenMart should address the food waste
issue. Ensure that your recommendations are informed and supported by your data analysis
and logical reasoning. Clearly explain the rationale behind each recommendation and how it
is expected to mitigate the food waste problem.
3) Assumptions and Limitations:
Explicitly identify any assumptions made during your analyses and acknowledge the
limitations of the data analysis in your business report. Explain the potential impact of these
assumptions and limitations on your findings and recommendations, ensuring that the
reader is fully informed of the context and constraints of your analysis.
Academic Integrity in COMM 1110 and UNSW
You may use AI software for brainstorming ideas initially, but your final submission should
primarily be your own work. Avoid relying on AI tools to generate your report. UNSW
employs a tool to detect AI-generated writing.
Always ensure your assignments are completed independently, without asking other people
to complete it on your behalf.
There are very few academic cheating cases in Assessment 3, and the university's integrity
department investigates these cases of academic misconduct, and if confirmed, students
may receive a grade of 0 for the course or face exclusion from UNSW.
Additional learning and Free Writing Feedback on your draft:
 Get individual feedback on you draft: https://www.student.unsw.edu.au/feedback-hub
Marking rubric for Assessment 4: Business Case Project - Part 2
Criteria
4 Fail
Pass
Credit
Distinction
High Distinction
1. Statistical
Analysis
40% Little to no understanding
of the dataset. Incorrect or
no use of statistical tools.
Lack of rationale in
variable selection. No
clear or incorrect
correlation or regression
analysis.
Basic understanding
of the dataset. Basic
use of statistical
tools. Some rationale
in variable selection.
Some correct
correlation or
regression analysis
but lacks depth.
Good understanding of
the dataset.
Appropriate use of
statistical tools. Clear
rationale in variable
selection. Mostly
correct and insightful
correlation and
regression analysis.
Excellent understanding
of the dataset.
Sophisticated use of
statistical tools. Very clear
and justified variable
selection. Comprehensive
and accurate correlation
and regression analysis,
with deep insights.
Outstanding
understanding of the
dataset. Expert use of
statistical tools.
Exceptional rationale in
variable selection.
Outstanding correlation
and regression analysis,
providing deep insights.
2. Applying the 7-
Step Ethical
Decision-Making
Framework
25% Fails to apply the
framework. No clear
position on the ethical
dilemma.
Basic application of
the framework. Clear
position on the ethical
dilemmas.
Good application of
the framework. Clear
and well-reasoned
position on the ethical
dilemma.
Excellent application of
the framework. Very
clear, well-reasoned, and
nuanced position on the
ethical dilemma.
Outstanding and
comprehensive
application of the
framework. Exceptionally
clear, well-reasoned, and
insightful position on the
ethical dilemma.
3. Developing
Solutions Using the
Analytical Toolbox
35% Lack of structure in the
argument. No clear
recommendations or
solutions. Fails to identify
assumptions and
limitations.
Basic structure in the
argument. Some
clear
recommendations or
solutions but lack
evidence. Identifies
some assumptions
and limitations.
Good structure in
argument. Clear and
evidence-backed
recommendations or
solutions. Good
identification of
assumptions and
limitations.
Excellent structure in
argument. Very clear,
evidence-backed, and
well-reasoned
recommendations or
solutions. Comprehensive
identification and
discussion of
assumptions and
limitations.
Outstanding structure in
argument. Exceptionally
clear, evidence-backed,
innovative, and well-
reasoned
recommendations or
solutions. Exceptional
identification and
insightful discussion of
assumptions and
limitations.