Students will launch the packaged food fairness investigation by testing a few sealed products, recording first data, and generating questions about whether package labels match what consumers actually get. They will build shared expectations for careful measurement, evidence-based claims, and revision with peer and expert feedback across the project.

Students will inspect real packaged foods, turn first impressions into testable investigation questions, and build a workable plan for collecting trustworthy weight data. They will practice choosing appropriate plots and statistics, decide how to document anomalies and outliers, and use peer critique to revise a shared method before moving into full data collection.

Students will collect reliable packaged food weight data, document measurement conditions and anomalies, build accurate graphs and summary statistics, and pass a midpoint quality check before moving into full fairness analysis.

Students will compare their packaged food distributions, interpret how center, spread, shape, and outliers affect a fairness verdict, revise their consumer recommendation through critique and expert feedback, and complete a polished showcase panel for the data walk.

Students will present and defend their final packaged food fairness findings to an authentic audience, then complete the closing reflection circle by naming a statistic they used, a claim they changed, and a way they grew in mathematics and collaboration.