Free Printable Causation and Correlation Worksheets for Year 9

Start with two variables that clearly move together, such as study time and test scores, and ask students whether one necessarily causes the other. Use scatter plots and contrasting real-world examples to establish the key rule: correlation can suggest a relationship, but causation requires stronger evidence and an explanation that addresses other possible variables.

Give students short scenarios and ask them to classify each relationship as causal, correlated but not proven causal, or coincidental. Follow with scatter-plot interpretation and prompts that require students to identify a possible lurking variable, not merely state that two variables are related.

The most common mistake is treating a strong correlation as proof that one variable caused the other. Students may also reverse the possible direction of cause and effect or overlook a third variable, such as weather affecting both ice cream sales and swimming activity.

Assign the worksheet as a digital quiz on Wayground or distribute it as a printable PDF. Every worksheet includes a complete answer key, and paper submissions can be scanned or captured for grading with the Wayground for Teachers app.

This topic supports Common Core's emphasis on interpreting bivariate data and evaluating associations between variables. It builds from reading tables and scatter plots toward explaining why an observed pattern may reflect a lurking variable rather than a direct cause.

Use simpler, familiar scenarios for students who need support and data-rich cases with confounding factors for advanced learners. On Wayground, selected students can receive Read Aloud or extended time, while alternate worksheet versions can use larger text or wider spacing without changing the statistical concept.

Students commonly begin formal work with correlation and causation in early high school; this collection is designed for Grade 9. At this level, the focus is usually on interpreting scatter plots, questioning causal claims, and recognizing possible lurking variables.