Mathematics · Grade 9

Active learning ideas

Scatter Plots and Correlation

Active learning works well for scatter plots because students need to physically gather and plot data to truly grasp how variables relate. Creating and interpreting scatter plots from real measurements helps turn abstract concepts like correlation into concrete understanding.

• Ontario Curriculum Expectations
• CCSS.MATH.CONTENT.8.SP.A.1
• CCSS.MATH.CONTENT.HSS.ID.B.6.A

• 35–50 min
• Pairs → Whole Class
• 4 activities

Activity 01

• Gallery Walk
• 45 min · Pairs

Data Collection: Class Height vs. Jump Height

Students measure each other's heights and vertical jump heights in pairs, record data on charts, then plot points on graph paper or digital tools. Groups discuss trends and label as positive, negative, or none. Share findings with the class.

Analyze the relationship between two variables as depicted in a scatter plot.

Facilitation Tip

During Data Collection: Height vs. Jump Height, circulate to ensure students measure accurately and record data consistently to avoid skewed results.

What to look for

Provide students with three different scatter plots, each showing a different type of correlation (positive, negative, none). Ask them to label each plot with the type of correlation and write one sentence explaining their reasoning for each.

• Understand
• Apply
• Analyze
• Create
• Relationship Skills
• Social Awareness

Activity 02

• Stations Rotation
• 50 min · Small Groups

Stations Rotation: Correlation Scenarios

Set up stations with printed datasets: sports stats, weather data, and consumer habits. At each, students plot data, draw trend lines, and rate correlation strength. Rotate every 10 minutes, then debrief as a class.

Differentiate between correlation and causation using real-world examples.

Facilitation Tip

In Station Rotation: Correlation Scenarios, provide rulers, grid paper, and colored pencils to help students sketch trend lines quickly and clearly.

What to look for

Present the scenario: 'Ice cream sales increase in the summer, and so do drowning incidents.' Ask students: 'Is there a correlation? Is there causation? Explain your answer using the terms correlation and causation.'

• Remember
• Understand
• Apply
• Analyze
• Self-Management
• Relationship Skills

Activity 03

• Gallery Walk
• 40 min · Small Groups

Digital Plotting: Correlation vs. Causation Debate

Provide datasets like TV hours vs. grades. Students use Google Sheets or Desmos to create scatter plots, identify correlations, then debate causation in small groups using evidence from plots. Present arguments whole class.

Predict the direction and strength of a correlation from a scatter plot.

Facilitation Tip

For Digital Plotting: Correlation vs. Causation Debate, prepare a shared digital tool so students can adjust plots in real time during discussions.

What to look for

Give students a small dataset (e.g., 5-7 pairs of numbers). Instruct them to create a scatter plot on a mini-whiteboard or paper. Then, ask them to write one sentence describing the correlation they observe and one sentence explaining why it is not necessarily causation.

• Understand
• Apply
• Analyze
• Create
• Relationship Skills
• Social Awareness

Activity 04

• Gallery Walk
• 35 min · Pairs

Prediction Challenge: Mystery Data

Show unlabeled scatter plots; students predict variables, strength, and direction in pairs. Reveal real contexts like temperature vs. cricket chirps, then create their own plots from new data.

Analyze the relationship between two variables as depicted in a scatter plot.

Facilitation Tip

During Prediction Challenge: Mystery Data, allow students to revise their predictions after plotting the full dataset, reinforcing iterative analysis.

What to look for

Provide students with three different scatter plots, each showing a different type of correlation (positive, negative, none). Ask them to label each plot with the type of correlation and write one sentence explaining their reasoning for each.

• Understand
• Apply
• Analyze
• Create
• Relationship Skills
• Social Awareness

A few notes on teaching this unit

Teach scatter plots by starting with concrete, relatable data students collect themselves, like height and jump height. Avoid jumping straight to technology; hands-on plotting builds intuition before digital tools enhance precision. Research shows students grasp correlation best when they first observe patterns in messy real data, then refine their thinking through structured peer discussion.

Students will confidently create scatter plots, identify correlation types, and explain their reasoning using data. They will also recognize when correlation does not imply causation and support their claims with evidence from the datasets.

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Watch Out for These Misconceptions

• During Data Collection: Height vs. Jump Height, watch for students assuming that taller people always jump higher.

  Have students plot the data and observe the scatter before drawing conclusions. Ask them to sketch a trend line and discuss outliers, reinforcing that correlation does not dictate individual outcomes.

• During Station Rotation: Correlation Scenarios, watch for students interpreting random scatter as 'no relationship' even when variables are weakly related.

  Provide datasets with subtle clusters or slight trends and guide students to sketch trend lines. Ask them to compare the strength of correlations across stations to refine their interpretation.

• During Prediction Challenge: Mystery Data, watch for students assuming all positive correlations form straight lines.

  Include at least one curved dataset in the mystery data. Ask students to describe the trend verbally and adjust their predictions after plotting, emphasizing that linearity is not required for correlation.

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Methods used in this brief

• Gallery Walk
• Stations Rotation