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. * 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:
Know that there are numbers that are not rational, and approximate them by rational numbers.

Standard:
Know that numbers that are not rational are called irrational. Understand informally that every number has a decimal expansion; for rational numbers show that the decimal expansion repeats eventually, and convert a decimal expansion which repeats eventually into a rational number.

Cluster:
Know that there are numbers that are not rational, and approximate them by rational numbers.

Standard:
Use rational approximations of irrational numbers to compare the size of irrational numbers, locate them approximately on a number line diagram, and estimate the value of expressions (e.g.,π^2). For example, by truncating the decimal expansion of √2, show that √2 is between 1 and 2, then between 1.4 and 1.5, and explain how to continue on to get better approximations.

Cluster:
Investigate patterns of association in bivariate data.

Standard:
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.