Search the California Content Standards

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 and evaluate random processes underlying statistical experiments.

Standard:
Understand statistics as a process for making inferences about population parameters based on a random sample from that population. *

Cluster:
Understand and evaluate random processes underlying statistical experiments.

Standard:
Understand statistics as a process for making inferences about population parameters based on a random sample from that population. *

Cluster:
Understand and evaluate random processes underlying statistical experiments.

Standard:
Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation. For example, a model says a spinning coin falls heads up with probability 0.5. Would a result of 5 tails in a row cause you to question the model? *

Cluster:
Understand and evaluate random processes underlying statistical experiments.

Standard:
Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation. For example, a model says a spinning coin falls heads up with probability 0.5. Would a result of 5 tails in a row cause you to question the model? *

Cluster:
Make inferences and justify conclusions from sample surveys, experiments, and observational studies.

Standard:
Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each. *

Cluster:
Make inferences and justify conclusions from sample surveys, experiments, and observational studies.

Standard:
Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each. *

Cluster:
Make inferences and justify conclusions from sample surveys, experiments, and observational studies.

Standard:
Use data from a sample survey to estimate a population mean or proportion; develop a margin of error through the use of simulation models for random sampling. *