Description
This item uses real basketball statistics to investigate data on scatterplots by finding trends, identifying clusters and outlier, writing the equation for trend lines, and using trend lines to make predictions. This item is included in the Data Math Madness bundle. For more basketball themed math items, visit my store!
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Highlights
Digital downloads
Grades
8th
Subjects
Standards
CCSS8.SP.A.1
CCSS8.SP.A.2
CCSS8.SP.A.3
Tags
Pages
2
Save even more with bundles
This bundle includes all of my basketball themed items that involve bivariate data (scatterplots and two way tables) at the 8th grade level along with the basketball mini posters and math madness bracket challenge. This bundle is designed to be used together throughout the week(s) of the college bas
Price $9.00Original Price $12.00Save $3.00
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Description
This item uses real basketball statistics to investigate data on scatterplots by finding trends, identifying clusters and outlier, writing the equation for trend lines, and using trend lines to make predictions. This item is included in the Data Math Madness bundle. For more basketball themed math items, visit my store!
Report this resource to TPT
Reported resources will be reviewed by our team. Report this resource to let us know if this resource violates TPT's content guidelines.
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Questions & Answers
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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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