Understands and applies descriptive statistics
Descriptive statistics involves describing and summarizing data. For example, for univariate (one-variable) data like test scores, we might describe the range of the data (lowest score to highest score), the mean score, or the standard deviation of the scores. For bivariate (two-variable) data like weight before and after a diet program, we might fit a line to the (before, after) data points and use the line to estimate and predict weight.
As societal demands for statistical reasoning increase, students in grades 9-12 need rich experiences to create, understand, and interpret statistical models with and without technology. These experiences should be built on their understandings of univariate and bivariate data developed in the middle grades. Students should collect, represent, and analyze numerical and categorical data.
Representations of data, both univariate and bivariate, should include histograms, box plots, scatterplots, bar graphs, line graphs, stem and leaf plots, frequency distributions, relative frequency distributions, and probability distributions. (Many of these representations should have been studied in middle school.) Instructional activities should ask students to compare and contrast these different representations.
Analysis of data should include the choice of appropriate representation, the study of measures of center and variability, transformations of univariate data, shape of distributions, outliers, regression, and correlation.