standard_description: Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.
problem_activity: Activity
The purpose of this activity is for students to approximate different parts of a graph with an appropriate line segment. This graph is from a previous activity, but students interact with it differently by sketching a linear function that models a certain part of the data. They take this model and consider its ability to predict input and output for other parts of the graph. This helps students think about subsets of data that might have different models from other parts of the data.
Identify students who draw in different lines for the first question to share during the Activity Synthesis.
Teacher Notes for IM 6–8 Math Accelerated
Due to how lessons and units are arranged in IM 6–8 Math Accelerated, students learn about scatter plots prior to this lesson instead of after this lesson. Be prepared to clarify that the graph shown in this activity is a time plot and not a scatter plot, and similar to the non linear scatter plots they encountered previously, a single line may not be a good fit for the entire data set.
Launch
Arrange students in groups of 2. Provide students with access to straightedges. Give students 3–5 minutes of quiet work time and then time to share their responses with their partner. Follow with a whole-class discussion.
Student Facing
In an earlier lesson, we saw this graph that shows the percentage of all garbage in the U.S. that was recycled between 1991 and 2013.
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Sketch a linear function that models the change in the percentage of garbage that was recycled between 1991 and 1995. For which years is the model good at predicting the percentage of garbage that is produced? For which years is it not as good?
Pick another time period to model with a sketch of a linear function. For which years is the model good at making predictions? For which years is it not very good?
Student Response
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Activity Synthesis
The purpose of this discussion is for students to understand that although you might find a good model for one part of a graph, that does not mean that model will work for other parts.
Select students previously identified to share their models. Display these for all to see throughout the entire discussion. Questions for discussion:
“How much does your model for 1991 to 1995 overestimate 1996? 1997?”
“If we drew in a single line to model 1997 to 2013, what would that line predict well? What would that line predict poorly?” (A single line modeling those years would reasonably predict the percent recycled from 1997 to 2010, but it wouldn’t be able to show how the percent recycled from 2011 to 2013 is decreasing.)
Conclude the discussion by telling students that there is a trade-off in number of years to include in the interval and accuracy. We could “connect the dots” and be accurate about everything, but then our model has limited use and is complicated with so many parts. (Just imaging writing an equation for each piece!)
Speaking: MLR8 Discussion Supports.
Use this routine to support whole-class discussion. For each model that is shared, ask students to summarize what they heard using mathematical language. Consider providing students time to restate what they hear to a partner, before selecting one or two students to share with the class. Ask the original speaker if their peer was accurately able to restate their thinking. Call students' attention to any words or phrases that helped to clarify the original statement. This will provide more students with an opportunity to speak, and better understand each model.
Design Principle(s): Support sense-making


aligns: no