Students help Leo, an ice cream truck owner, analyze sales data by creating and using a linear model. Using sliders to adjust slope and intercept, they minimize model error, find the best-fit line, and predict sales for new temperatures—discovering how data models are built and used in the real world.
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.
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.
Students will learn how to build and apply a linear model to represent and predict relationships between two quantitative variables. By creating a line of best fit from scatter-plot data and using it to estimate unknown values, students will understand how mathematical models can describe real-world patterns and support data-driven predictions.
Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line.
All 8.SP.A.2 activities →Use the equation of a linear model to solve problems in the context of bivariate measurement data, interpreting the slope and intercept. *For example, in a linear model for a biology experiment, interpret a slope of 1.5 cm/hr as meaning that an additional hour of sunlight each day is associated with an additional 1.5 cm in mature plant height*.
All 8.SP.A.3 activities →
More interactive, auto-graded activities on the same standards and topics.
Snack Stand Showdown is a Grade 8 statistics lab where students run a Field Day snack stand and use real data to decide what to charge and how much to buy. They build scatter plots, fit lines of best fit, price from profit curves, place a budgeted vendor order, and read two-way tables. A connected, auto-graded arc covering the full 8.SP standard cluster.
Students build a linear model from a price–demand scatterplot, then use it to predict demand, revenue, and profit at different price points. They analyze curves and determine the price that maximizes profit. A perfect real-world 8th-grade activity for scatterplots, linear modeling, and financial reasoning.
Students analyze real-world scatterplots and linear models to interpret bivariate data. They write equations using given slopes and y-intercepts, explain what these values mean in context, make predictions, and evaluate model limitations. Aligned to CCSS 8.SP.A.3 and ideal for statistics practice or assessment.
Help Leo, an ice cream truck owner, uncover how weather affects his sales! Students plot real data points to create a scatter plot, identify trends, and spot outliers. This engaging, hands-on activity builds understanding of correlation, trend lines, and data interpretation using a fun, real-world scenario.
Students help Leo, an ice cream truck owner, build a linear model to predict sales! Using interactive sliders to adjust slope and intercept, they create the best-fit line, minimize model error, and discover how straight lines can model real-world data relationships.
Students collect and summarize data from a live classroom survey on topics like pets, siblings, and school routines. As they enter values, interactive charts update in real time. Students then analyze the graphs and answer summary questions. A fun way to learn data collection and interpretation!
