Unit 6, Lesson 7
Observing More Patterns in Scatter Plots
Grade 8
7.1
Warm-up
Notice and Wonder: Non-linear Scatter Plot
What do you notice? What do you wonder?
A scatterplot. Horizontal, from 250000 to 450000, by 50000’s, labeled oil production, thousands of tons. Vertical, from 0 to 100, by 20’s, labeled crude oil import price, dollars. 23 dots, trend downward and right in a curve.
7.3
Activity
Clustering
Find groups of 2 or 3 scatter plots that share something in common that the others do not. What do they have in common?
Plot A, points start at 0 comma 40 and trend down and to the right.
Plot B has 2 sets of points, 1 starts near the origin and trends up and to the right. The second starts near 3 comma 25 and trends up and to the right.
Plot C has 2 sets of points, 1 starts near the origin and trends up and to the right. The second starts near the origin and trends down and to the right
Plot D points starts near 0 comma 40 and trends down and to the right toward 24 negative 20, but there are no points between x = 6 and x = 12.
Student Lesson Summary
Sometimes a scatter plot shows an association that is not linear:
In this scatter plot, the data initially shows a negative trend then later a positive trend. Because the variables appear to be associated, but not in a linear way, we call this a non-linear association. In later grades, you will study functions that can be models for non-linear associations.
Sometimes in a scatter plot we can see separate groups of points.
A scatterplot with two groups of points. The first begins near the origin and trends up and to the right toward 8 comma 13. Second group begins near 3 comma 25 and trends up and right toward 9 comma 45.
A scatterplot with two groups of points. The first begins near the origin and trends up and to the right toward 8 comma 13. Second group begins near 3 comma 25 and trends up and right toward 9 comma 45. Each group is circled.
We call these groups “clusters.” Clusters often appear when multiple patterns are present within the data. There may be subgroups within the overall data set that affect the variables.
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