Statistics and Probability Standards CONCLUSIONS S.IC INTERPRETING CATEGORICAL AND Understand and evaluate random processes underlying QUANTITATIVE DATA S.ID statistical experiments. Summarize, represent, and interpret data on a single count or measurement variable. S.IC.1 Understand statistics as a process for making inferences S.ID.4 Use the mean and standard deviation of a data set to fit it to a about population parameters based on a random sample from normal distribution and to estimate population percentages. that population.★ Recognize that there are data sets for which such a procedure is not S.IC.2 Decide if a specified model is consistent with results from a appropriate. Use calculators, spreadsheets, and tables to estimate given data-generating process, e.g., using simulation. For example, a areas under the normal curve.★ 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?★ Summarize, represent, and interpret data on two categorical and quantitative variables. MAKING INFERENCES AND JUSTIFYING CONCLUSIONS, S.ID.6 Represent data on two quantitative variables on a scatter plot, CONT’D Make inferences and justify conclusions from sample surveys, and describe how the variables are related.★ experiments, and observational studies. a. Fit a function to the data; use functions fitted to data to solve S.IC.3 Recognize the purposes of and differences among sample problems in the context of the data. Use given functions, or surveys, experiments, and observational studies; explain how choose a function suggested by the context. Emphasize linear, randomization relates to each.★ quadratic, and exponential models. (A2, M3) Informally assess the fit of a function by discussing residuals. S.IC.4 Use data from a sample survey to estimate a population mean b. (A2, M3) or proportion; develop a margin of error through the use of simulation models for random sampling.★ Interpret linear models. S.IC.5 Use data from a randomized experiment to compare two S.ID.9 Distinguish between correlation and causation.★ treatments; use simulations to decide if differences between sample statistics are statistically significant.★ MAKING INFERENCES AND JUSTIFYING S.IC.6 Evaluate reports based on data.★
Statistics and Probability Standards INTERPRETING CATEGORICAL AND QUANTITATIVE DATA S.ID Summarize, represent, and interpret data on a single count or measurement variable. S.ID.4 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.★ Summarize, represent, and interpret data on two categorical and quantitative variables. S.ID.6 Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.★ a. Fit a function to the data; use functions fitted to data to solve problems in the context of the data. Use given functions, or choose a function suggested by the context. Emphasize linear, quadratic, and exponential models. (A2, M3) b. Informally assess the fit of a function by discussing residuals. (A2, M3) Interpret linear models. S.ID.9 Distinguish between correlation and causation.★ MAKING INFERENCES AND JUSTIFYING CONCLUSIONS S.IC Understand and evaluate random processes underlying statistical experiments. S.IC.1 Understand statistics as a process for making inferences about population parameters based on a random sample from that population.★ S.IC.2 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?★ MAKING INFERENCES AND JUSTIFYING CONCLUSIONS, CONT’D Make inferences and justify conclusions from sample surveys, experiments, and observational studies. S.IC.3 Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each.★ S.IC.4 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.★ S.IC.5 Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between sample statistics are statistically significant.★ S.IC.6 Evaluate reports based on data.★