Learning Goal
Part of: Investigate patterns of association in bivariate data — 1 of 4 cluster items
Construct and interpret scatter plots for bivariate measurement data
**8.SP.A.1**: 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.
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8.SP.A.1: 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.
What you'll learn
- Construct a scatter plot from a table of bivariate measurement data by choosing appropriate axes, scales, and plotting ordered pairs
- Identify and describe patterns of association between two quantities shown in a scatter plot, including positive association, negative association, and no association
- Distinguish between linear association and nonlinear association in a scatter plot
- Identify and interpret clusters and outliers in a scatter plot and explain what they suggest about the data
- Use the language of association (not correlation) to describe the overall relationship between two variables in a real-world context
Slides
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Slides
In development
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