Scatter Plots Stations Activity | Lines of Best Fit, Correlation & Analyze
Make Sense of Math
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Grade Levels
8th - 9th, Homeschool
Subjects
Resource Type
Standards
CCSS8.SP.A.1
CCSS8.SP.A.2
CCSS8.SP.A.3
Formats Included
- PDF
Pages
14 pages
Make Sense of Math
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Description
These math stations delve into scatter plots with a focus on correlation and informally analyzing lines of best fit. Students will create, analyze, estimate and explain. Students will develop a deep understanding of this content after completing these math stations.
The following stations are included:
- Create and Analyze: Students will create and analyze a scatter plot. Noticing correlation, outliers and clusters.
- Lines of Best Fit: Students are given a scatter plot and are to informally draw and write an equation for a line of best fit. This is done by estimating not by actually calculating. They will then use the line of best fit to make predictions.
- Sketching Correlations: Students will sketch various scatter plots given certain correlations.
- Correlation Situations: Given situations, students will determine the type of correlation and will also create situations for certain correlations.
- Letter Writing: Students will write a letter to their friend about everything they learned about lines of best fit.
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Make Sense of Math
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Total Pages
14 pages
Answer Key
Included
Teaching Duration
N/A
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Standards
to see state-specific standards (only available in the US).
CCSS8.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.
CCSS8.SP.A.2
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.
CCSS8.SP.A.3
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.
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