Search the California Content Standards

Cluster:
Reason quantitatively and use units to solve problems. [Foundation for work with expressions, equations and functions]

Standard:
Define appropriate quantities for the purpose of descriptive modeling.*

Cluster:
Reason quantitatively and use units to solve problems. [Foundation for work with expressions, equations, and functions]

Standard:
Define appropriate quantities for the purpose of descriptive modeling. *

Cluster:
Reason quantitatively and use units to solve problems. [Foundation for work with expressions, equations, and functions]

Standard:
Choose a level of accuracy appropriate to limitations on measurement when reporting quantities. *

Cluster:
Reason quantitatively and use units to solve problems. [Foundation for work with expressions, equations and functions]

Standard:
Choose a level of accuracy appropriate to limitations on measurement when reporting quantities.*

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.

Cluster:
Investigate patterns of association in bivariate data.

Standard:
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.

Cluster:
Investigate patterns of association in bivariate data.

Standard:
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.

Cluster:
Investigate patterns of association in bivariate data.

Standard:
Understand that patterns of association can also be seen in bivariate categorical data by displaying frequencies and relative frequencies in a two-way table. Construct and interpret a two-way table summarizing data on two categorical variables collected from the same subjects. Use relative frequencies calculated for rows or columns to describe possible association between the two variables. For example, collect data from students in your class on whether or not they have a curfew on school nights and whether or not they have assigned chores at home. Is there evidence that those who have a curfew also tend to have chores?

Cluster:
Understand similarity in terms of similarity transformations.

Standard:
Verify experimentally the properties of dilations given by a center and a scale factor: A dilation takes a line not passing through the center of the dilation to a parallel line, and leaves a line passing through the center unchanged.

Cluster:
Understand similarity in terms of similarity transformations.

Standard:
Verify experimentally the properties of dilations given by a center and a scale factor: A dilation takes a line not passing through the center of the dilation to a parallel line, and leaves a line passing through the center unchanged.