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Skills available for Arizona high school math standards

Standards are in black and IXL math skills are in dark green. Hold your mouse over the name of a skill to view a sample problem. Click on the name of a skill to practice that skill.

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N Number and Quantity

A Algebra

F Functions

G Geometry

S Statistics and Probability

  • S-ID Interpreting Categorical and Quantitative Data

    • S Summarize, represent, and interpret data on a single count or measurement variable

    • S Summarize, represent, and interpret data on two categorical and quantitative variables

      • S-ID.5 Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data.

      • S-ID.6 Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.

    • S Interpret linear models

      • S-ID.7 Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.

      • S-ID.8 Compute (using technology) and interpret the correlation coefficient of a linear fit.

      • S-ID.9 Distinguish between correlation and causation.

  • S-IC Making Inferences and Justifying Conclusions

    • S Understand and evaluate random processes underlying statistical experiments

    • S 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 parameters are significant.

      • S-IC.6 Evaluate reports based on data.

  • S-CP Conditional Probability and the Rules of Probability

  • S-MD Using Probability to Make Decisions

    • S Calculate expected values and use them to solve problems

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

      • S-MD.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.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 Use probability to evaluate outcomes of decisions

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

        • S-MD.5.a Find the expected payoff for a game of chance.

        • S-MD.5.b Evaluate and compare strategies on the basis of expected values.

      • S-MD.6 Use probabilities to make fair decisions (e.g., drawing by lots, using a random number generator).

      • S-MD.7 Analyze decisions and strategies using probability concepts (e.g., product testing, medical testing, pulling a hockey goalie at the end of a game).

CM Contemporary Mathematics

  • CM-DM Discrete Mathematics

    • CM Understand and apply vertex-edge graph topics

      • CM-DM.1 Study the following topics related to vertex-edge graphs: Euler circuits, Hamilton circuits, the Travelling Salesperson Problem (TSP), minimum weight spanning trees, shortest paths, vertex coloring, and adjacency matrices.

      • CM-DM.2 Understand, analyze, and apply vertex-edge graphs to model and solve problems related to paths, circuits, networks, and relationships among a finite number of elements, in real-world and abstract settings.

      • CM-DM.3 Devise, analyze, and apply algorithms for solving vertex-edge graph problems.

      • CM-DM.4 Extend work with adjacency matrices for graphs, such as interpreting row sums and using the nth power of the adjacency matrix to count paths of length n in a graph.