Search the California Content Standards

Cluster:
Summarize, represent, and interpret data on two categorical and quantitative variables. [Linear focus; discuss general principle.]

Standard:
Represent data on two quantitative variables on a scatter plot, and describe how the variables are related. * Informally assess the fit of a function by plotting and analyzing residuals. *

Cluster:
Summarize, represent, and interpret data on two categorical and quantitative variables. [Linear focus; discuss general principle.]

Standard:
Represent data on two quantitative variables on a scatter plot, and describe how the variables are related. * Fit a linear function for a scatter plot that suggests a linear association. *

Cluster:
Summarize, represent, and interpret data on two categorical and quantitative variables. [Linear focus; discuss general principle.]

Standard:
Represent data on two quantitative variables on a scatter plot, and describe how the variables are related. * Fit a linear function for a scatter plot that suggests a linear association. *

Cluster:
Interpret linear models.

Standard:
Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data. *

Cluster:
Interpret linear models.

Standard:
Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data. *

Cluster:
Interpret linear models.

Standard:
Compute (using technology) and interpret the correlation coefficient of a linear fit. *

Cluster:
Interpret linear models.

Standard:
Compute (using technology) and interpret the correlation coefficient of a linear fit. *

Cluster:
Interpret linear models.

Standard:
Distinguish between correlation and causation. *

Cluster:
Interpret linear models.

Standard:
Distinguish between correlation and causation. *

Cluster:
Summarize, represent, and interpret data on a single count or measurement variable.

Standard:
Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages. Recognize that there are data sets for which such a procedure is not appropriate. Use calculators, spreadsheets, and tables to estimate areas under the normal curve. *