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Skills available for Illinois 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

  • 9-12.S.ID.1 Represent data with plots on the real number line (dot plots, histograms, and box plots).

  • 9-12.S.ID.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.

  • 9-12.S.ID.3 Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).

  • 9-12.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.

  • 9-12.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.

  • 9-12.S.ID.6 Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.

  • 9-12.S.ID.7 Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.

  • 9-12.S.ID.8 Compute (using technology) and interpret the correlation coefficient of a linear fit.

  • 9-12.S.ID.9 Distinguish between correlation and causation.

  • 9-12.S.IC.1 Understand statistics as a process for making inferences about population parameters based on a random sample from that population.

  • 9-12.S.IC.2 Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation.

  • 9-12.S.IC.3 Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each.

  • 9-12.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.

  • 9-12.S.IC.5 Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between parameters are significant.

  • 9-12.S.IC.6 Evaluate reports based on data.

  • 9-12.S.CP.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.

  • 9-12.S.CP.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.

  • 9-12.S.CP.4 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.

  • 9-12.S.CP.5 Recognize and explain the concepts of conditional probability and independence in everyday language and everyday situations.

  • 9-12.S.CP.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.

  • 9-12.S.CP.7 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.

  • 9-12.S.CP.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.

  • 9-12.S.CP.9 Use permutations and combinations to compute probabilities of compound events and solve problems.

  • 9-12.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.

  • 9-12.S.MD.2 Calculate the expected value of a random variable; interpret it as the mean of the probability distribution.

  • 9-12.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.

  • 9-12.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.

  • 9-12.S.MD.5 Weigh the possible outcomes of a decision by assigning probabilities to payoff values and finding expected values.

    • 9-12.S.MD.5a Find the expected payoff for a game of chance.

    • 9-12.S.MD.5b Evaluate and compare strategies on the basis of expected values.

  • 9-12.S.MD.6 Use probabilities to make fair decisions (e.g., drawing by lots, using a random number generator).

  • 9-12.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).