Line Graph Analysis
Trends Over Time · Level 4 Statistics
Ngā Whāinga Akoranga · Learning Intentions
- Read and interpret line graphs showing change over time
- Identify trends — increasing, decreasing, stable — from a line graph
- Make predictions based on patterns in data
- Compare multiple data sets plotted on the same graph
Paearu Angitu · Success Criteria
- I can describe the direction of a trend using evidence from the graph
- I can read a specific value from a line graph accurately
- I can make a prediction by extending a trend — and explain my reasoning
- I can compare two lines on the same graph and say which is higher and when
Hononga Marautanga · Curriculum Alignment
Curriculum alignment for this handout has not yet been verified against the live curriculum statements. A generated placeholder that stood here was removed on 2026-08-29 because it matched no real statement.
Whakataukī
"Kia whakatōmuri te haere whakamua"
I walk backwards into the future with my eyes fixed on my past.
Our tīpuna understood that to move forward wisely, we must learn from what has come before. Line graphs help us see patterns across time — like tracking the seasons, watching the tides, or understanding growth.
Kauwhata 1 · Wellington Average Monthly Temperature (sample data)
Sample data built for graphing practice — a realistic Wellington seasonal shape, not a measured record. Real monthly figures are published by NIWA if you want to graph the genuine article.
| Month | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Temp (°C) | 19 | 20 | 17 | 14 | 12 | 10 | 9 | 10 | 12 | 14 | 16 | 18 |
1. What was the warmest month in Wellington? What temperature?
2. What was the coldest month? How much colder than the warmest month?
3. Between which two months did the temperature drop the most? By how many degrees?
4. PREDICT: If this seasonal pattern continues, what temperature would you expect in January 2025? Explain.
Kauwhata 2 · Rainfall — Auckland vs Wellington (mm/month, sample data)
Sample data built for graphing practice. It is realistic in shape but it is not a measured record, so do not use it to settle which city is really wetter — the two are closer than most people expect. For the real figures, look up NIWA’s climate normals for each city.
| Month | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Auckland (mm) | 72 | 68 | 80 | 95 | 105 | 120 | 130 | 120 | 100 | 90 | 80 | 76 |
| Wellington (mm) | 65 | 55 | 73 | 80 | 110 | 115 | 125 | 115 | 90 | 80 | 73 | 68 |
1. Which city had more rainfall in June? How much more?
2. In which months were the two cities closest in rainfall? (There is more than one — check every month before you answer.) How can you tell from the graph?
3. Which city had the single wettest month? Name the month and the rainfall amount.
4. Overall, which city gets more rain in this dataset? Back up your answer with calculations or data.
Kauwhata 3 · Student Test Scores (10-week term progress)
| Week | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
|---|---|---|---|---|---|---|---|---|---|---|
| Aroha (%) | 54 | 58 | 60 | 63 | 66 | 70 | 73 | 75 | 78 | 82 |
| Tāne (%) | 70 | 68 | 72 | 69 | 74 | 76 | 74 | 78 | 79 | 80 |
| Class Avg (%) | 60 | 61 | 63 | 65 | 66 | 68 | 69 | 71 | 72 | 74 |
1. Who made the most progress from Week 1 to Week 10? Calculate the exact improvement.
2. At which week did Aroha's score overtake the class average?
3. Calculate Tāne's improvement from Week 1 to Week 10 as a percentage change. Show your working.
4. If Aroha's trend continues, predict her score at Week 15. Show how you worked it out.
Aronga Mātauranga Māori
Our tīpuna were sophisticated observers of trends over time. Maramataka — the Māori lunar calendar — encoded centuries of observation about how temperature, rainfall, stars, and seasons pattern together. Long before thermometers and rain gauges, Māori communities tracked climate data through kaupeka (branch patterns), flight of birds, and the behaviours of fish. Reading a line graph is the same cognitive skill: look for pattern, identify change, predict forward.
When iwi use historical population data (like Māori population recovery graphs post-1896) or river health trend data in resource consent hearings, they are doing exactly what this activity practises — reading trend lines as evidence to understand the past and argue for the future.
Ngā Rauemi Tautoko · Support Materials
Resources already provided:
- This handout with data tables — plot your own graphs in the grid spaces
- Ruler (essential — line graphs require straight point-to-point lines)
- Coloured pens or pencils — use different colours for each line in multi-line graphs
- Calculator (permitted for percentage change calculations)
Aronga Rerekē · Differentiated Pathways
Tīmata · Entry Level
Complete Graph 1 only (Wellington temperature). Plot the line graph and answer questions 1 and 2. Focus on reading values accurately from your graph.
Paerewa · On Level
Complete all three graphs. Answer all questions. Show working for the percentage change in Graph 3.
Tūāpae · Extension
Complete all sections. Find a real NIWA dataset for your region and plot a fourth graph. Write a paragraph interpreting the trend and its environmental or social significance for Aotearoa.