Search the California Content Standards

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:
Summarize, represent, and interpret data on a single count or measurement variable.

Standard:
Represent data with plots on the real number line (dot plots, histograms, and box plots). *

Cluster:
Summarize, represent, and interpret data on a single count or measurement variable.

Standard:
Represent data with plots on the real number line (dot plots, histograms, and box plots). *

Cluster:
Summarize, represent, and interpret data on a single count or measurement variable.

Standard:
Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets. *

Cluster:
Summarize, represent, and interpret data on a single count or measurement variable.

Standard:
Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets. *

Cluster:
Summarize, represent, and interpret data on a single count or measurement variable.

Standard:
Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers). *

Cluster:
Summarize, represent, and interpret data on a single count or measurement variable.

Standard:
Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers). *

Cluster:
Summarize, represent, and interpret data on two categorical and quantitative variables. [Linear focus; discuss general principle.]

Standard:
Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data. *

Cluster:
Summarize, represent, and interpret data on two categorical and quantitative variables. [Linear focus; discuss general principle.]

Standard:
Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data. *