Search the California Content Standards

Cluster:
Understand independence and conditional probability and use them to interpret data.

Standard:
Recognize and explain the concepts of conditional probability and independence in everyday language and everyday situations. For example, compare the chance of having lung cancer if you are a smoker with the chance of being a smoker if you have lung cancer. *

Cluster:
Use the rules of probability to compute probabilities of compound events in a uniform probability model.

Standard:
Find the conditional probability of A given B as the fraction of B’s outcomes that also belong to A, and interpret the answer in terms of the model. *

Cluster:
Use the rules of probability to compute probabilities of compound events in a uniform probability model.

Standard:
Apply the Addition Rule, P(A or B) = P(A) + P(B) – P(A and B), and interpret the answer in terms of the model. *

Cluster:
Use the rules of probability to compute probabilities of compound events in a uniform probability model.

Standard:
(+) Apply the general Multiplication Rule in a uniform probability model, P(A and B) = P(A)P(B|A) = P(B)P(A|B), and interpret the answer in terms of the model. *

Cluster:
Use the rules of probability to compute probabilities of compound events in a uniform probability model.

Standard:
(+) Use permutations and combinations to compute probabilities of compound events and solve problems. *

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:
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:
Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages. Recognize that there are data sets for which such a procedure is not appropriate. Use calculators, spreadsheets, and tables to estimate areas under the normal curve. *

Cluster:
Summarize, represent, and interpret data on two categorical and quantitative variables.

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. *