From Pattern to Prediction: Modeling Ice Cream Sales

In this interactive 8th-grade statistics lab, students explore how math can be used to model and predict real-world data. Leo, an ice cream truck owner, wants to understand how temperature affects his daily sales. Students use a scatter plot of his data to create a linear model by adjusting the slope (m) and y-intercept (b) with sliders. As they fine-tune the line, the model error updates dynamically, helping them find the best-fit line with an error below 12.

Once they’ve created their model, students use their equation, y = mx + b, to make predictions for new temperatures, learning how a mathematical model can represent data and estimate unknown values.

🧭 In this lab, students will:

• Analyze a real-world dataset showing temperature vs. ice cream sales
• Use interactive sliders to adjust the slope and y-intercept of a line
• Observe how the model error changes as the line fits better
• Identify when the model has a strong fit (error below 12)
• Write the equation of their line of best fit (y = mx + b)
• Substitute new x-values (temperatures) to predict sales for unknown data points
• Reflect on how mathematical models help in data analysis and forecasting



Aligned with CCSS 8.SP.A.2 and 8.SP.A.3, this hands-on, visual lab helps students understand how linear models summarize data trends and support data-driven predictions—just like real data analysts, scientists, and business owners do every day. Perfect for classroom, blended, or independent learning, this activity turns abstract math into an engaging, real-world experience.