Search the California Content Standards

Cluster:
Investigate chance processes and develop, use, and evaluate probability models.

Standard:
Develop a probability model and use it to find probabilities of events. Compare probabilities from a model to observed frequencies; if the agreement is not good, explain possible sources of the discrepancy. Develop a probability model (which may not be uniform) by observing frequencies in data generated from a chance process. For example, find the approximate probability that a spinning penny will land heads up or that a tossed paper cup will land open-end down. Do the outcomes for the spinning penny appear to be equally likely based on the observed frequencies?

Cluster:
Investigate chance processes and develop, use, and evaluate probability models.

Standard:
Find probabilities of compound events using organized lists, tables, tree diagrams, and simulation. Understand that, just as with simple events, the probability of a compound event is the fraction of outcomes in the sample space for which the compound event occurs.

Cluster:
Investigate chance processes and develop, use, and evaluate probability models.

Standard:
Find probabilities of compound events using organized lists, tables, tree diagrams, and simulation. Represent sample spaces for compound events using methods such as organized lists, tables and tree diagrams. For an event described in everyday language (e.g., “rolling double sixes”), identify the outcomes in the sample space which compose the event.

Cluster:
Investigate chance processes and develop, use, and evaluate probability models.

Standard:
Find probabilities of compound events using organized lists, tables, tree diagrams, and simulation. Design and use a simulation to generate frequencies for compound events. For example, use random digits as a simulation tool to approximate the answer to the question: If 40% of donors have type A blood, what is the probability that it will take at least 4 donors to find one with type A blood?

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:
Use probability to evaluate outcomes of decisions. [Introductory; apply counting rules.]

Standard:
(+) Use probabilities to make fair decisions (e.g., drawing by lots, using a random number generator). *

Cluster:
Use probability to evaluate outcomes of decisions. [Introductory; apply counting rules.]

Standard:
(+) Use probabilities to make fair decisions (e.g., drawing by lots, using a random number generator). *