Search the California Content Standards

Cluster:
Construct and compare linear, quadratic, and exponential models and solve problems. [Linear and exponential]

Standard:
Construct linear and exponential functions, including arithmetic and geometric sequences, given a graph, a description of a relationship, or two input-output pairs (include reading these from a table). *

Cluster:
Construct and compare linear, quadratic, and exponential models and solve problems.

Standard:
Construct linear and exponential functions, including arithmetic and geometric sequences, given a graph, a description of a relationship, or two input-output pairs (include reading these from a table). *

Cluster:
Construct and compare linear, quadratic, and exponential models and solve problems.

Standard:
Observe using graphs and tables that a quantity increasing exponentially eventually exceeds a quantity increasing linearly, quadratically, or (more generally) as a polynomial function. *

Cluster:
Construct and compare linear, quadratic, and exponential models and solve problems. [Linear and exponential]

Standard:
Observe using graphs and tables that a quantity increasing exponentially eventually exceeds a quantity increasing linearly, quadratically, or (more generally) as a polynomial function. *

Cluster:
Interpret expressions for functions in terms of the situation they model. [Linear and exponential of form f(x) = b^x + k]

Standard:
Interpret the parameters in a linear or exponential function in terms of a context. *

Cluster:
Interpret expressions for functions in terms of the situation they model.

Standard:
Interpret the parameters in a linear or exponential function in terms of a context. * [Linear and exponential of form f(x) = b^x + k]

Cluster:
Interpret expressions for functions in terms of the situation they model.

Standard:
Apply quadratic functions to physical problems, such as the motion of an object under the force of gravity. CA *

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.