Learning Domain: Statistics and Probability: Conditional Probability and the Rules of Probability

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.*

Degree of Alignment: Not Rated (0 users)

Learning Domain: Statistics and Probability: Conditional Probability and the Rules of Probability

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.*

Degree of Alignment: Not Rated (0 users)

Learning Domain: Statistics and Probability: Conditional Probability and the Rules of Probability

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.*

Degree of Alignment: Not Rated (0 users)

Learning Domain: Statistics and Probability: Conditional Probability and the Rules of Probability

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.*

Degree of Alignment: Not Rated (0 users)

Learning Domain: Statistics and Probability: Conditional Probability and the Rules of Probability

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.*

Degree of Alignment: Not Rated (0 users)

Learning Domain: Statistics and Probability: Conditional Probability and the Rules of Probability

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.*

Degree of Alignment: Not Rated (0 users)

Learning Domain: Statistics and Probability: Making Inferences and Justifying Conclusions

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

Degree of Alignment: Not Rated (0 users)

Learning Domain: Statistics and Probability: Making Inferences and Justifying Conclusions

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?*

Degree of Alignment: Not Rated (0 users)

Learning Domain: Statistics and Probability: Making Inferences and Justifying Conclusions

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

Degree of Alignment: Not Rated (0 users)

Learning Domain: Statistics and Probability: Making Inferences and Justifying Conclusions

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.*

Degree of Alignment: Not Rated (0 users)

Learning Domain: Statistics and Probability: Making Inferences and Justifying Conclusions

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

Degree of Alignment: Not Rated (0 users)

Learning Domain: Statistics and Probability: Making Inferences and Justifying Conclusions

Standard: Evaluate reports based on data.*

Degree of Alignment: Not Rated (0 users)

Learning Domain: Statistics and Probability: Interpreting Categorical and Quantitative Data

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.*

Degree of Alignment: Not Rated (0 users)

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.*

Degree of Alignment: Not Rated (0 users)

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.*

Degree of Alignment: Not Rated (0 users)

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?*

Degree of Alignment: Not Rated (0 users)

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.*

Degree of Alignment: Not Rated (0 users)

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.*

Degree of Alignment: Not Rated (0 users)

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.*

Degree of Alignment: Not Rated (0 users)

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

Standard: Evaluate reports based on data.*

Degree of Alignment: Not Rated (0 users)

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”).*

Degree of Alignment: Not Rated (0 users)

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.*

Degree of Alignment: Not Rated (0 users)

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.*

Degree of Alignment: Not Rated (0 users)

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.*

Degree of Alignment: Not Rated (0 users)

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.*

Degree of Alignment: Not Rated (0 users)

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.*

Degree of Alignment: Not Rated (0 users)

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.*

Degree of Alignment: Not Rated (0 users)