Massachusetts flagMassachusetts: Statistics and Probability - Interpreting Categorical and Quantitative Data Math Standards

11 standards · 3 domains

SUMMARIZE, REPRESENT, AND INTERPRET DATA ON A SINGLE COUNT OR MEASUREMENT VARIABLE. USE CALCULATORS, SPREADSHEETS, AND OTHER TECHNOLOGY AS APPROPRIATE.

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

SUMMARIZE, REPRESENT, AND INTERPRET DATA ON TWO CATEGORICAL AND QUANTITATIVE VARIABLES.

  • S-ID.B.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.B.6.a Fit a linear function to the data and use the fitted function to solve problems in the context of the data. Use functions fitted to data or choose a function suggested by the context. Emphasize linear and exponential models.
  • S-ID.B.6.b Informally assess the fit of a function by plotting and analyzing residuals.
  • S-ID.B.6.c Fit a linear function for a scatter plot that suggests a linear association.

INTERPRET LINEAR MODELS.

  • S-ID.C.7 Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.
  • S-ID.C.8 Compute (using technology) and interpret the correlation coefficient of a linear fit.
  • S-ID.C.9 Distinguish between correlation and causation.

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