CCSS.Math.Content.8.SP.A.1

Math8th GradeInvestigate patterns of association in bivariate data.

The standard

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.

Common Core State Standards for Mathematics · Statistics and Probability

What this standard means

Students need to plot paired numerical data on a coordinate grid and use the graph to describe the relationship between the two variables. They should name what they see, such as positive association, negative association, no clear association, clusters, outliers, linear patterns, and curved patterns.

Mastery looks like reading a scatter plot with evidence, not just saying “it goes up.” Students should point to the data pattern and explain what it means in context. Common trouble spots are mixing up correlation with cause, ignoring outliers, using uneven scales, and describing a pattern without referring to both variables.

Ways to teach it

  • Have students measure arm span and height, make a class scatter plot, and label clusters, outliers, and the overall association.
  • Ask students to write: What does this scatter plot suggest, and what can it not prove?
  • Show a scatter plot for 30 seconds, then have students identify association type, one outlier, and one cluster on an exit ticket.
  • Use local weather data to compare daily high temperature and ice cream sales, then discuss what the pattern might and might not mean.

Plan a lesson for CCSS.Math.Content.8.SP.A.1

Generate a complete lesson plan aligned to this standard, with objectives, activities, and materials. Free, no account needed.

Related standards

Standard text verified against corestandards.org on July 10, 2026.

Page updated July 10, 2026.

Send Feedback