Weather Data Detectives

Overview

Students investigate a small set of continuous numerical data: daily temperatures. They organise measurements, represent them on a line plot, and interpret what the distribution shows. The lesson develops statistical thinking by connecting numerical data with visual patterns and evidence-based statements.

Learning intentions

• WALT identify continuous numerical data and describe what it measures.
• WALT organise temperature data and represent it on a suitable visual display.
• WALT interpret clusters, spread, gaps and unusual values.
• WALT support conclusions with evidence from a data display.

Success criteria

• I can explain why temperature is continuous numerical data.
• I can accurately plot data using a scale and labels.
• I can describe patterns in the data using statistical language.
• I can answer questions and refer to values in the display as evidence.

Curriculum links

• Statistics 1 — developing knowledge, visualisation and interpretation of continuous numerical data.
• Mathematics and Statistics — using data displays to notice, describe and communicate patterns.
• Te Mātaiaho Mathematics and Statistics — higher-order thinking and challenge through purposeful mathematical investigation.
• Communication and collaboration — explaining mathematical thinking and responding to others’ interpretations.

Lesson structure (40 minutes)

1. 0–5 min · Hook and notice. Display a visual of two weather forecasts with temperatures from 8°C to 24°C using the opening weather comparison slide. Ask: “What could we learn from these numbers, and how could we show them so the pattern is easy to see?” Students make a quiet observation, then share one notice and one question with a partner.

2. 5–11 min · Build knowledge. Use the data vocabulary and example slides to introduce continuous numerical data as measurements that can take any value within a range, such as temperature, height or time. Model the difference between a list of measurements and a visual display, revising range, minimum, maximum, cluster, gap and unusual value. Students identify which examples are continuous and justify one choice.

3. 11–15 min · Model visualisation. Show a class data set of 25 temperatures, such as: 8, 9, 10, 10, 11, 12, 12, 13, 13, 14, 14, 15, 15, 15, 16, 16, 17, 17, 18, 18, 19, 20, 21, 22, 24. Model constructing a line plot on the gradually revealed line-plot example. Think aloud about choosing equal intervals, placing points accurately, and labelling the measurement and unit. Students check where the lowest, highest and most common values would appear.

4. 15–28 min · Pair investigation. Distribute the temperature data investigation sheet to pairs. Students use the provided data to create a line plot, then answer questions about the minimum, maximum, range, cluster, gap and any unusual value. Partners must compare their plots, correct errors and write two evidence-based observations. Circulate and ask: “What does this part of the display tell you?” and “Which values support your statement?”

5. 28–35 min · Interpret and discuss. Display the interpretation prompts and comparison slide. Pairs compare their observations with another pair and decide whether the statement “The weather was usually mild” is supported by the data. They must agree on a response using at least two values or features of the plot. Invite several pairs to share different interpretations and discuss how a conclusion can be reasonable without being the only possible conclusion.

6. 35–40 min · Plenary and exit check. Students complete the question stems poster as a discussion reference, choosing one stem such as “I notice…”, “I can compare…” or “I predict…”. Individually, they write: “The data shows… because…” and include one accurate value or feature from their plot. Collect responses as the exit check.

Resources

• the weather data investigation slide deck
• the temperature data investigation sheet
• the question stems poster
• Whiteboard and markers
• Pencils, rulers and coloured pencils
• Projector or interactive display
• Prepared temperature data set
• A4 paper for pair discussion

Assessment

• During modelling, check whether students can distinguish a measurement from a count and explain why temperature is continuous.
• During pair work, check scale choice, accurate plotting, labels, and use of terms such as cluster, gap, spread and unusual value.
• Use the individual exit response to assess whether students can make a supported interpretation rather than simply report a single number.

Differentiation

• Support students with a pre-drawn axis, marked intervals, a reduced data range, and sentence starters: “Most values are between…”, “The cluster is…”, and “I know this because…”.
• Pair students strategically and provide a vocabulary bank with simple definitions and visual examples.
• For students needing extension, ask them to explain how the interpretation might change if the highest value were removed, or to design a second display that could represent the same data.
• Read instructions aloud, use clear visual modelling, and allow students to discuss ideas orally before recording them. Check that all students can see the display and provide a ruler or enlarged worksheet where needed.