CCSS.Math.Content.HSS-ID.B.6b

MathGrades 9–12Interpreting Categorical and Quantitative Data

The standard

Informally assess the fit of a function by plotting and analyzing residuals.

Common Core State Standards for Mathematics · Summarize, represent, and interpret data on two categorical and quantitative variables

What this standard means

Students need to compare a data set to a chosen model by looking at residuals. They should calculate actual minus predicted values, plot those residuals against the x-values, and decide whether the model is doing a reasonable job.

Mastery looks like noticing patterns, not just saying points are close. A good fit has residuals scattered randomly around zero. A curved pattern, fan shape, or clusters suggest the model is missing something. Students often mix up residuals with y-values, forget the sign, or treat one large residual as proof the whole model is bad.

Ways to teach it

  • Give pairs a scatterplot, line of fit, and table, then have them compute residuals with sticky notes and build a residual plot.
  • Ask students to write: What would a residual plot look like if a linear model is a poor choice, and why?
  • Show three residual plots and have students label each as random scatter, curved pattern, or fan shape, with one sentence of evidence.
  • Use school commute time and distance data, fit a line, then check whether the residuals suggest distance alone predicts commute time well.

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Related standards

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

Page updated July 10, 2026.

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