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.c] - Fit a linear function for a scatter plot that suggests a linear association.*

Resources:


  • Linear association
    Two variables have a linear association if a scatter plot of the data can be well approximated by a line.
  • Linear function
    A function with an equation of the form y = mx + b, where m and b are constants
  • Scatter plot
    A graph in the coordinate plane representing a set of bivariate data. For example, the heights and weights of a group of people could be displayed on a scatter plot.

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.

Successor Standards:

No Successor Standards found.

Same Level Standards:

  • AI.S-ID.B.6.b
    Informally assess the fit of a function by plotting and analyzing residuals.*
  • AI.S-ID.C.7
    Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.*
  • AI.S-ID.C.8
    Compute (using technology) and interpret the correlation coefficient of a linear fit.*