ASSESSMENT GUIDE

COMM5000

Data Literacy

Housing Market Trends &

Affordability: A Data-Driven

Business & Policy Analysis

Milestone 1 InformationTerm 1, 2025

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Table of Contents

Assessment Summary .................................................................................................................................................................................. 2

Assessment Administrative Details (Check Course Outline/Moodle) ...................................................................................................... 3

Turnitin .................................................................................................................................................................................................................................................. 3

Late Submissions ................................................................................................................................................................................................................................. 3

Extensions ............................................................................................................................................................................................................................................ 3

Special Consideration ........................................................................................................................................................................................................................... 3

CASE STUDY INFORMATION-- Housing Market Trends & Affordability Project Statement .................................................................. 4

Business and Economic Context .................................................................................................................................................................................. 4

The Dataset: Australian Housing Market Overview .................................................................................................................................................... 5

MILESTONE 1: Preliminary Insight Development ...................................................................................................................................... 7

Report details .................................................................................................................................................................................................................. 7

Description of Milestone 1 assessment task ............................................................................................................................................................... 7

Question 1: Price Variability Across States .......................................................................................................................................................................................... 7

Question 2: Relationship Between House Size & Price ........................................................................................................................................................................ 8

Question 3: Identifying Outliers in Housing Prices ................................................................................................................................................................................ 8

Question 4: Comparing Property Prices by Building Type .................................................................................................................................................................... 8

Final Report Submission Expectation .......................................................................................................................................................................... 8

Student Guidelines for Writing the Report ............................................................................................................................................................................................ 9

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Assessment Summary

Assessment Task Weighting Due Date* Course Learning

Outcomes

Milestone 1: Case Study Preliminary Insight Development (due in

Week 4 20%)

Online Quiz in Week 4 during seminar time (TBA in Moodle)

15%

5%

Week 4 (Friday 5PM) 1, 2

Milestone 2: Case study project proposal

Online Quiz in Week 7 during seminar time (TBA in Moodle)

15%

5%

Week 7 (Friday 11:59PM) 1, 2, 3, 4

Case Study business report

Online Quiz in Week 10 in Seminar time (TBA in Moodle)

40%

20%

Week 11 (Friday 11:59 PM) 2, 3, 4, 5

* Due dates are set at Australian Eastern Standard/Daylight Time (AEST/AEDT). If you are located in a different time-zone, you can use the time and date converter.

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Assessment Administrative Details (Check Course Outline/Moodle)

Turnitin

Turnitin is an originality checking and plagiarism prevention tool that enables checking of submitted written work for

improper citation or misappropriated content. Each Turnitin assignment is checked against other students' work, the

Internet and key resources selected by your Course Coordinator.

If you are instructed to submit your assessment via Turnitin, you will find the link to the Turnitin submission in your

Moodle course site. You can submit your assessment well before the deadline and use the Similarity Report to

improve your academic writing skills before submitting your final version.

You can find out more information on the Turnitin information site for students.

Late Submissions

The parameters for late submissions are outlined in the UNSW Assessment Implementation Procedure. For

COMM5000, if you submit your assessments after the due date, you will incur penalties for late submission unless you

have Special Consideration (see below). Late submission is 5% per day (including weekends), calculated from the

marks allocated to that assessment (not your grade). Assessments will not be accepted more than 5 days late.

Extensions

You are expected to manage your time to meet assessment due dates. If you do require an extension to your

assessment, please make a request as early as possible before the due date via the special consideration portal on

myUNSW (My Student profile > Special Consideration). You can find more information on Special Consideration and

the application process below. Lecturers and tutors do not have the ability to grant extensions.

Special Consideration

Special consideration is the process for assessing the impact of short-term events beyond your control (exceptional

circumstances), on your performance in a specific assessment task.

What are circumstances beyond my control?

These are exceptional circumstances or situations that may:

• Prevent you from completing a course requirement,

• Keep you from attending an assessment,

• Stop you from submitting an assessment,

• Significantly affect your assessment performance.

Available here is a list of circumstances that may be beyond your control. This is only a list of examples, and your

exact circumstances may not be listed.

You can find more detail and the application form on the Special Consideration site, or in the UNSW Special

Consideration Application and Assessment Information for Students.

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CASE STUDY INFORMATION-- Housing Market Trends &

Affordability Project Statement

Business and Economic Context

The housing market is a critical sector influencing government policies, financial institutions, real estate

investors, and urban planners. Property prices, affordability, and market trends impact economic stability,

investment risks, and infrastructure development.

Government housing agencies need to assess affordability trends to develop policies for first-time

homebuyers and low-income families. Real estate investors and developers require insights into high-growth

suburbs to determine where to build or invest. Financial institutions and banks analyse property data to

evaluate mortgage risks and loan eligibility. Urban planners and infrastructure authorities depend on market

insights to plan future housing projects based on demand and population growth. These stakeholders rely

on data-driven analysis to make informed decisions about housing policies, market investments, and

economic development.

In major cities like Sydney, Melbourne, and Brisbane, housing affordability is a growing concern. With property

prices outpacing wage growth, many struggle to enter the market, increasing the need for government

intervention and affordable housing initiatives. Monitoring housing trends helps policymakers craft effective

policies to improve homeownership access and ensure fair housing opportunities.

Beyond affordability, real estate is a key driver of employment in construction, finance, and property services.

The Reserve Bank of Australia (RBA) adjusts interest rates in response to market shifts, influencing mortgage

holders and consumer spending. Rapid price surges may require regulatory adjustments to maintain

economic stability. Analysing property data enables decision-makers to anticipate market changes and

implement necessary financial measures.

For many Australians, property is both a home and a long-term investment. Housing prices impact wealth

accumulation, retirement planning, and intergenerational wealth transfer. Investors and financial institutions

rely on market trends to assess risks and identify opportunities. Disparities between urban and regional

property markets also shape internal migration as people and businesses seek affordability and economic

prospects.

The Australian housing market is also shaped by global factors such as economic trends, immigration

policies, and foreign investment. Economic downturns, trade shifts, and crises like COVID-19 have all

impacted supply and demand. Tracking housing prices allows businesses and governments to anticipate

risks and develop strategies for market resilience.

Studying housing prices is more than tracking property values—it is a fundamental part of economic planning,

investment strategies, and urban development. By analysing real estate trends, decision-makers can shape

policies that drive economic growth and improve the quality of life for Australians.

https://www.youtube.com/watch?v=P2chYfJ4cRs

https://www.youtube.com/watch?v=LBKIloe1Zuc

Your role as Data Scientist

As a Housing Market Analyst, your role begins with an Exploratory Data Analysis (EDA) using descriptive

statistics and visualization techniques to uncover patterns, variations, and key trends in housing prices. This

is the foundation of data-driven decision-making, where you will summarize distributions, identify outliers,

and assess relationships within the data.

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Once a clear understanding of the dataset has been established, the focus will shift toward formulating key

hypotheses, allowing us to test theories and claims about the factors driving property prices. This step will

help in identifying potential causal relationships, which will later be examined using statistical modelling and

inferential techniques. Ultimately, this process will enable us to move beyond simple observations and

establish evidence-based insights that support strategic decision-making in the housing market.

The Dataset: Australian Housing Market Overview

You will be working with a dataset containing real estate property records. The dataset includes

information on property characteristics, pricing, and location details. The key categories of information in

the dataset are:

Location Data → State, suburb, street name, postcode.

Market Information → Market price of the property.

Property Characteristics → Building type, number of bedrooms, number of bathrooms.

Structural Features → Living area size, car area, outdoor area.

Access your sample data

Each student is allocated a randomly selected sample of properties distributed over suburbs across the

states of VIC, QLD, NSW.

Step 1: Open the Google Sheets Link

Click on the Google Sheets link: https://docs.google.com/spreadsheets/d/1M4j2zpbNx65L7l-jBa2qD_zB- Jrw71fli8QvqxtWiRc/edit?usp=sharing

The “Student Lookup” sheet should open automatically.

Step 2: Enter Your Student ID in cell B1 just in front of "Enter Your Student ID:"

Type your Student ID exactly as given (e.g., 5530530).

Press Enter or click outside the cell

Step 3: Download and save Your Assigned Data

Click File → Download.

Select Microsoft Excel (.xlsx) or CSV (.csv).

Troubleshooting Common Issues

❌ Data does not appear:

✔ Ensure your Student ID is correct (check for typos).

✔ Reload the Google Sheets page and try again.

✔ Contact me at: [email protected]

❌ Seeing a #REF! error?

✔ Click “Allow Access” when prompted by Google Sheets.

✔ Ensure you are logged into the correct Google account.

Additional notes: The sheet ‘Assignments’ is the master data file. You do not have to worry about it or

access it.

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MILESTONE 1: Preliminary Insight Development

Report details

Week 4, Sunday 11:59PM

15%

Report: This is individual work. Reports will be checked for plagiarism.

1000-1500 words (not including tables, graphs, and references)

Via Moodle course site

Description of Milestone 1 assessment task

For this first Exploratory Data Analysis (EDA), your role as a Housing Market Analyst requires you to examine

key trends in the real estate market and report back to stakeholders who rely on data-driven insights for

decision-making. These stakeholders include government policymakers, real estate investors, financial

institutions, and urban planners, each of whom requires a deeper understanding of price trends, affordability,

and investment risks. Your analysis will focus on answering four critical questions that will help these

stakeholders:

✔ Understand price variations and market stability across states.

✔ Analyse the relationship between house size and price to determine key value drivers.

✔ Detect extreme property prices (outliers) that may mislead market analysis.

✔ Compare pricing differences across different property types (houses, apartments, townhouses).

The findings from your report will directly inform investment strategies, housing policies, and urban planning

decisions.

Question 1: Price Variability Across States

Stakeholder Concern: A key concern for policymakers and investors is whether housing prices remain

consistent across different states or if some regions experience more significant fluctuations than others.

While some argue that property values vary widely due to economic differences, job markets, and local

demand, others believe that the housing market follows a more stable national trend. Understanding these

price patterns is essential for designing housing affordability strategies and assessing investment risks. This

insight will help stakeholders identify where property investments are more secure and where affordability

interventions may be necessary.

Your Task:

• Compare price distributions across states using summary statistics (mean, median, IQR, standard

deviation).

• Identify which states show the highest and lowest price variability.

• Use box plots or histograms to illustrate differences in price spread.

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Question 2: Relationship Between House Size & Price

Stakeholder Concern: There is a common belief that larger homes always command higher prices, but

this may not hold true in all markets. Property value is influenced by various factors, including location,

demand, and the availability of land, which may sometimes outweigh the impact of size. Developers,

investors, and buyers need to understand how much house size contributes to price and whether prioritizing

square footage is an effective strategy. Your analysis will explore the relationship between house size and

market price, providing insight into whether larger homes consistently lead to higher valuations or if other

factors play a more significant role.

Your Task:

• Examine the correlation between house size (sqm) and price.

• Create a scatter plot with a trendline to visualize patterns.

• Compare findings across different suburbs or states to identify variations.

Question 3: Identifying Outliers in Housing Prices

Stakeholder Concern: Irregular pricing in the housing market can distort affordability assessments and

mislead buyers, investors, and policymakers. Some properties may be priced significantly above or below

typical market values due to luxury features, distressed sales, or unusual market conditions. Identifying these

outliers is important for refining overall market analysis and ensuring that decision-makers have an accurate

understanding of pricing trends. Your role is to determine which properties deviate significantly from the

general price range and assess whether these extreme values impact overall market assessments. This will

provide insights into whether price distortions are common in specific regions or property types.

Your Task:

• Define outliers using statistical methods (e.g., IQR, Z-score).

• Use a box plot to highlight extreme values in the dataset.

• Discuss whether outliers should be removed or analysed separately.

Question 4: Comparing Property Prices by Building Type

Stakeholder Concern: Property values vary not only by location but also by building type. Some types of

properties, such as detached houses, may appreciate differently compared to apartments or townhouses.

These differences may result from factors such as land value, maintenance costs, and buyer demand.

Investors need to understand which property types offer the best returns, while urban planners must

anticipate housing demand trends to guide infrastructure development. This analysis will help stakeholders

understand how housing demand is shifting and where future development should be prioritized.

Your Task:

• Compare median prices across different building types.

• Use a box plot to visualize price distributions for each category.

• Identify whether some building types show higher price variations than others.

Final Report Submission Expectation

Your role as a Housing Market Analyst is to provide clear, data-driven insights, not lengthy descriptions.

Focus on answering the questions concisely and meaningfully while ensuring your findings are useful to

stakeholders. Your report should be concise and structured, focusing on clear numerical summaries,

visualizations, and insightful interpretations.

Word Limit: 1,500 words (maximum)

Report Length: 3-4 pages (excluding tables & figures)

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Submission Format: TWO separate files: (1) Report in PDF or Word Document (2) Excel Work file OR other

programming codes.

Key Focus: Be concise, structured, and insightful—avoid unnecessary descriptions.

Student Guidelines for Writing the Report

Each section should directly respond to the stakeholder’s concerns and should be formatted as follows:

Executive Summary (Maximum 150 Words)

• Clearly state the key findings from your analysis.

• Summarize the main trends in housing prices, affordability, and property types.

• Highlight one or two key insights that stakeholders would find useful.

Exploratory Data Analysis (EDA) (total 800-1000 words)

Each question should be addressed in ¾ page (200-250 words max), ensuring clarity and conciseness. The

response to each question must include:

a) Numerical Summary

• Provide one concise table summarizing key statistics.

• Ensure figures are formatted clearly for easy readability.

b) Data Visualization

• Use one relevant and well-labelled chart per question.

• Include a short caption explaining the visualization.

c) Interpretation & Insights

• Provide a short but insightful explanation of the results.

• Address the stakeholder’s concerns directly—explain why the data matters.

• Avoid unnecessary explanations—focus on key takeaways.

Key Insights & Business Implications (Max 250 Words)

• Summarize the most important insights from the four questions.

• Discuss why these insights are relevant for policymakers, investors, or planners.

• Highlight one key recommendation based on your findings.

Report Structure & Writing Style

• Use clear section headings and a logical flow.

• Keep writing concise—avoid unnecessary details.

• Use bullet points sparingly, only when summarizing key insights.

• Ensure charts and tables are integrated into the discussion, not just added as attachments.

• Use professional, neutral language suitable for a business audience.

Common Mistakes to Avoid

Too much description: Avoid over-explaining statistical methods—focus on results.

Missing context: Always explain why the data is important for stakeholders.

Disorganized structure: Keep responses structured using the

Numerical Summary → Visualization →

Interpretation format.

Charts without explanations: Every graph must be accompanied by a brief interpretation.

Overuse of text: Stick to key points—don’t exceed 1,500 words.

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