Gizmos for Idaho - Mathematics: Statistics and Probability (Content Standards adopted 2022)

This correlation lists the recommended Gizmos for this state's curriculum standards. Click any Gizmo title below for more information.

S.ID: : Interpreting Categorical and Quantitative Data

S.ID.A: : Summarize, represent, and interpret data on a single count or measurement variable. Use calculators, spreadsheets, and other technology as appropriate.

S.ID.A.2: : Represent measurement data with plots on the real number line (dot plots, histograms, and box plots).

S.ID.A.3: : Compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different variables, using statistics appropriate to the shape of the distribution for each measurement variable.

S.ID.A.4: : Interpret differences in shape, center, and spread in the context of the variables accounting for possible effects of extreme data points (outliers) for measurement variables.

S.ID.A.5: : 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.

S.ID.B: : Summarize, represent, and interpret data on two categorical and quantitative variables.

S.ID.B.7: : Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.

S.ID.B.7.a: : Fit a linear function to data where a scatter plot suggests a linear relationship and use the fitted function to solve problems in the context of the data.

S.ID.B.7.c: : Informally assess the fit of a function by plotting and analyzing residuals.

S.ID.C: : Interpret linear models.

S.ID.C.8: : Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.

S.ID.C.9: : Compute (using technology) and interpret the linear correlation coefficient.

S.ID.C.10: : Distinguish between (linear) correlation and causation.

S.IC: : Making Inferences and Justifying Conclusions

S.IC.A: : Understand and evaluate random processes underlying statistical studies. Use calculators, spreadsheets, and other technology as appropriate.

S.IC.A.1: : Understand statistics as a process for making inferences about population parameters based on a random sample from that population.

S.IC.B: : Make inferences and justify conclusions from sample surveys, experiments, and observational studies.

S.IC.B.3: : Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each.

S.IC.B.4: : Use data from a sample survey to estimate a population mean or proportion and a margin of error.

S.IC.B.6: : Evaluate reports of statistical information based on data.

S.CP: : Conditional Probability and the Rules of Probability

S.CP.A: : Understand independence and conditional probability and use them to interpret data from simulations or experiments.

S.CP.A.2: : Demonstrate understanding 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.

S.CP.A.3: : Understand the conditional probability of A given B as P(intersection of 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.

S.CP.A.5: : Recognize and explain the concepts of conditional probability and independence in everyday language and everyday situations.

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

S.CP.B.6: : 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 mode.

S.CP.B.8: : Apply the general Multiplication Rule in a uniform probability model P(intersection of A and B) = P(A)P(B|A) = P(B)P(A|B), and interpret the answer in terms of the model.

S.CP.B.9: : Use permutations and combinations to compute probabilities of compound events and solve problems.

S.MD: : Using Probability to Make Decisions

S.MD.A: : Calculate expected values and use them to solve problems.

S.MD.A.1: : Define a random variable for a quantity of interest by assigning a numerical value to each event in a sample space; graph the corresponding probability distribution using the same graphical displays as for data distributions.

S.MD.A.2: : Calculate the expected value of a random variable; interpret it as the mean of the probability distribution of the variable.

S.MD.A.3: : Develop a probability distribution for a random variable defined for a sample space in which theoretical probabilities can be calculated; find the expected value.

S.MD.A.4: : Develop a probability distribution for a random variable defined for a sample space in which probabilities are assigned empirically; find the expected value.

S.MD.B: : Use probability to evaluate outcomes of decisions.

S.MD.B.5: : Weigh the possible outcomes of a decision by assigning probabilities to payoff values and finding expected values.

S.MD.B.5.a: : Find the expected payoff for a game of chance.

S.MD.B.5.b: : Evaluate and compare strategies on the basis of expected values.

Correlation last revised: 2/25/2022

Idaho - Mathematics: Statistics and Probability

Content Standards | Adopted: 2022

S.ID: : Interpreting Categorical and Quantitative Data

S.IC: : Making Inferences and Justifying Conclusions

S.CP: : Conditional Probability and the Rules of Probability

S.MD: : Using Probability to Make Decisions