Lesson 1 of 3

Data Detective: Housing in Aotearoa

Understanding the crisis through numbers

Ako | Learning Intentions

Know: The difference between median and mean house prices and why we use percentages to compare data over time.
Do: Create a time-series graph using Stats NZ data to show housing affordability trends.
Understand: How mathematical data reflects real-world social issues (Inequality).

He Kōrero Timatanga - Introduction

Everyone talks about how expensive houses are in New Zealand. But what does the data actually say? As mathematicians, our job is to look past the headlines and find the evidence.

Discussion Starter

"If your parents bought a house for $200,000 in 2000, and it's worth $1,000,000 today, did they make an $800,000 profit?"

Consider: Inflation, interest payments, maintenance, and the buying power of money.

Part 1: The Context (Whakawhanaungatanga)

Before looking at numbers, we need to understand the human side.

Watch: Short video on the history of NZ housing (e.g., State Housing in the 1940s vs today).
Brainstorm: What factors affect house prices? (Location, Size, Supply, Interest Rates).

Part 2: Data Exploration

We will use a simplified dataset from Stats NZ containing:

Median House Price (National)
Median Household Income
Years: 2000 - 2024

📊 Data Visualization Exercise

Students plot "Median House Price" vs "Median Income" on the same timeline.

Guiding Question: The lines are moving apart. Calculate the ratio of House Price to Income for 2000 vs 2024.

                        Ratio (2000) = $180,000 / $45,000 = 4.0

                        Ratio (2024) = $900,000 / $110,000 = 8.1

Conclusion: Houses are mathematically twice as hard to buy today relative to income.

Part 3: Telling the Story

For NCEA Level 1 (AS 91945), simply doing the calculation isn't enough. You must interpret it in context.

Task: Write a paragraph summarizing your findings. Use the phrase "The data suggests that..." and refer to your calculated ratios.

Kaiako Notes

Be sensitive to students' housing situations. Focus on the systemic data rather than individual family circumstances. This is an opportunity to discuss equity vs equality.