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

### CCSS.Math.Content.HSS-ID: : Interpreting Categorical and Quantitative Data

CCSS.Math.Content.HSS-ID.A: : Summarize, represent, and interpret data on a single count or measurement variable

CCSS.Math.Content.HSS-ID.A.1: : Represent data with plots on the real number line (dot plots, histograms, and box plots).

CCSS.Math.Content.HSS-ID.A.2: : 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.

CCSS.Math.Content.HSS-ID.A.3: : Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).

CCSS.Math.Content.HSS-ID.A.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.

CCSS.Math.Content.HSS-ID.B: : Summarize, represent, and interpret data on two categorical and quantitative variables

CCSS.Math.Content.HSS-ID.B.6: : Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.

CCSS.Math.Content.HSS-ID.B.6a: : Fit a function to the data; use functions fitted to data to solve problems in the context of the data.

CCSS.Math.Content.HSS-ID.B.6b: : Informally assess the fit of a function by plotting and analyzing residuals.

CCSS.Math.Content.HSS-ID.B.6c: : Fit a linear function for a scatter plot that suggests a linear association.

CCSS.Math.Content.HSS-ID.C: : Interpret linear models

CCSS.Math.Content.HSS-ID.C.7: : Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.

CCSS.Math.Content.HSS-ID.C.8: : Compute (using technology) and interpret the correlation coefficient of a linear fit.

CCSS.Math.Content.HSS-ID.C.9: : Distinguish between correlation and causation.

### CCSS.Math.Content.HSS-IC: : Making Inferences and Justifying Conclusions

CCSS.Math.Content.HSS-IC.A: : Understand and evaluate random processes underlying statistical experiments

CCSS.Math.Content.HSS-IC.A.1: : Understand statistics as a process for making inferences about population parameters based on a random sample from that population.

CCSS.Math.Content.HSS-IC.A.2: : Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation.

CCSS.Math.Content.HSS-IC.B: : Make inferences and justify conclusions from sample surveys, experiments, and observational studies

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

CCSS.Math.Content.HSS-IC.B.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.

CCSS.Math.Content.HSS-IC.B.5: : Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between parameters are significant.

### CCSS.Math.Content.HSS-CP: : Conditional Probability and the Rules of Probability

CCSS.Math.Content.HSS-CP.A: : Understand independence and conditional probability and use them to interpret data

CCSS.Math.Content.HSS-CP.A.2: : 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.

CCSS.Math.Content.HSS-CP.A.3: : 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.

CCSS.Math.Content.HSS-CP.A.5: : Recognize and explain the concepts of conditional probability and independence in everyday language and everyday situations.

CCSS.Math.Content.HSS-CP.B: : Use the rules of probability to compute probabilities of compound events in a uniform probability model

CCSS.Math.Content.HSS-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 model.

CCSS.Math.Content.HSS-CP.B.8: : 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.

CCSS.Math.Content.HSS-CP.B.9: : Use permutations and combinations to compute probabilities of compound events and solve problems.

### CCSS.Math.Content.HSS-MD: : Using Probability to Make Decisions

CCSS.Math.Content.HSS-MD.A: : Calculate expected values and use them to solve problems

CCSS.Math.Content.HSS-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.

CCSS.Math.Content.HSS-MD.A.2: : Calculate the expected value of a random variable; interpret it as the mean of the probability distribution.

CCSS.Math.Content.HSS-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.

CCSS.Math.Content.HSS-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.

CCSS.Math.Content.HSS-MD.B: : Use probability to evaluate outcomes of decisions

CCSS.Math.Content.HSS-MD.B.5: : Weigh the possible outcomes of a decision by assigning probabilities to payoff values and finding expected values.

CCSS.Math.Content.HSS-MD.B.5a: : Find the expected payoff for a game of chance.

CCSS.Math.Content.HSS-MD.B.5b: : Evaluate and compare strategies on the basis of expected values.

CCSS.Math.Content.HSS-MD.B.6: : Use probabilities to make fair decisions (e.g., drawing by lots, using a random number generator).

CCSS.Math.Content.HSS-MD.B.7: : Analyze decisions and strategies using probability concepts (e.g., product testing, medical testing, pulling a hockey goalie at the end of a game).

Correlation last revised: 8/22/2022