Standards Map

Mathematics > Course Model Algebra I (Traditional Pathway) > Interpreting Categorical and Quantitative Data
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Mathematics | Course : Model Algebra I (Traditional Pathway)

Domain - Interpreting Categorical and Quantitative Data

Cluster - Summarize, represent, and interpret data on two categorical and quantitative variable.

[AI.S-ID.B.6.b] - Informally assess the fit of a function by plotting and analyzing residuals.*

Resources:


  • Function
    A mathematical relation for which each element of the domain corresponds to exactly one element of the range.

Predecessor Standards:

  • 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.
  • 8.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.
  • 8.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.

Successor Standards:

No Successor Standards found.

Same Level Standards:

  • AI.S-ID.B.6.a
    Fit a linear function to the data and use the fitted function to solve problems in the context of the data. Use functions fitted to data or choose a function suggested by the context (emphasize linear and exponential models).
  • AI.S-ID.B.6.c
    Fit a linear function for a scatter plot that suggests a linear association.*