High School Statistics and Probability (Wisconsin Standards)

Interpreting Categorical and Quantitative Data (SP.ID)

• M.SP.ID.A.1 Represent data with dot plots, histograms and box plots.
• M.SP.ID.A.2 Compare center and spread of data sets using statistics suited to their shape.
• M.SP.ID.A.3 Interpret differences in shape, center and spread between data sets in context, considering outliers.
• M.SP.ID.A.4 Fit data to a normal distribution with mean and standard deviation and know when that is not appropriate.
• M.SP.ID.B.5 Summarize two-category data in two-way tables and interpret relative frequencies.
• M.SP.ID.B.6 Make a scatter plot of two numeric variables and describe their relationship.
  • a. Fit a function to data and use it to solve problems.
  • b. Judge fit informally using residuals.
  • c. Fit a linear function where the association looks linear.
• M.SP.ID.C.7 Interpret the slope and intercept of a linear model in context.
• M.SP.ID.C.8 Use technology to find a correlation coefficient and interpret it.
• M.SP.ID.C.9 Tell correlation apart from causation.

Making Inferences and Justifying Conclusions (SP.IC)

• M.SP.IC.A.1 Understand statistics as inference about population parameters from a random sample.
• M.SP.IC.A.2 Decide whether a model is consistent with results from a data-generating process, e.g. by simulation.
• M.SP.IC.B.3 Know the purposes of and differences between sample surveys, experiments and observational studies and the role of randomization.
• M.SP.IC.B.4 Use sample survey data to estimate a population mean or proportion and a margin of error by simulation.
• M.SP.IC.B.5 Compare two treatments with data from a randomized experiment, using simulation to judge whether differences matter.
• M.SP.IC.B.6 Evaluate reports based on data.

Conditional Probability and the Rules of Probability (SP.CP)

• M.SP.CP.A.1 Describe events as subsets of the sample space, including unions, intersections and complements.
• M.SP.CP.A.2 Know that two events are independent when the probability of both equals the product of their probabilities.
• M.SP.CP.A.3 Understand conditional probability P(A|B) and interpret independence with it.
• M.SP.CP.A.4 Use two-way tables or Venn diagrams to show two categorical variables and judge association and independence.
• M.SP.CP.A.5 Explain conditional probability and independence in everyday language and situations.
• M.SP.CP.B.6 Find P(A|B) from a two-way table or Venn diagram and interpret it.
• M.SP.CP.B.7 Apply the Addition Rule and interpret the answer.
• M.SP.CP.B.8 Use the general Multiplication Rule in a uniform model, e.g. with a tree diagram.
• M.SP.CP.B.9 Use permutations and combinations to find probabilities of compound events.

Using Probability to Make Decisions (SP.MD)

• M.SP.MD.A.1 Define a random variable and graph its probability distribution.
• M.SP.MD.A.2 Find the expected value of a random variable as the mean of its distribution.
• M.SP.MD.A.3 Build a theoretical probability distribution and find its expected value.
• M.SP.MD.A.4 Build an empirical probability distribution and find its expected value.
• M.SP.MD.B.5 Weigh outcomes of decisions using expected values of payoffs.
  • a. Work out the expected payoff of a game of chance.
  • b. Compare strategies using expected values.
• M.SP.MD.B.6 Make fair decisions with probability, e.g. a random draw.
• M.SP.MD.B.7 Analyze decisions and strategies with probability, e.g. testing or investment choices.