Search the California Content Standards

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. *

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

Standard:
Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between parameters are significant. *

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

Standard:
Evaluate reports based on data. *

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

Standard:
Describe events as subsets of a sample space (the set of outcomes) using characteristics (or categories) of the outcomes, or as unions, intersections, or complements of other events (“or,” “and,” “not”). *

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

Standard:
Understand that two events A and B are independent if the probability of A and B occurring together is the product of their probabilities, and use this characterization to determine if they are independent. *

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

Standard:
Understand the conditional probability of A given B as P(A and B)/P(B), and interpret independence of A and B as saying that the conditional probability of A given B is the same as the probability of A, and the conditional probability of B given A is the same as the probability of B. *

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

Standard:
Construct and interpret two-way frequency tables of data when two categories are associated with each object being classified. Use the two-way table as a sample space to decide if events are independent and to approximate conditional probabilities. For example, collect data from a random sample of students in your school on their favorite subject among math, science, and English. Estimate the probability that a randomly selected student from your school will favor science given that the student is in tenth grade. Do the same for other subjects and compare the results. *

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. *