Students compute measures of center (mean, median, mode) and measures of variability (range, interquartile range, mean absolute deviation) for paired data sets such as Orchard A vs. Orchard B and Summer vs. Winter dot plots. Students construct and interpret box plots and dot plots and answer comparison questions about which data set shows more variability and about outliers. Students calculate mean absolute deviation for both distributions (e.g., summer vs. winter) and use those values when discussing differences in spread.

Students create dot plots for sample data (candy activity) and construct frequency tables and percentages to compare a sample to the population. Students examine a histogram and a box plot for food-truck sales and are given calculated measures of center (mean = 25) and a measure of variability (mean absolute deviation = 8.75). Students compute sample means in the word-length activity and compare those sample means to the population mean (about 3.6), explicitly exploring sampling variability.

Students are asked to create and study stacked dot plots and box plots to compare two populations and to identify overlapping data values (e.g., pumpkin, zucchini, and adoption examples). Students compute the mean and mean absolute deviation for each data set (pumpkin and zucchini examples show step-by-step MAD calculations). Students compute the ratio formed by (difference of the means) divided by the larger mean absolute deviation and use that number to judge the degree of overlap, with guided interpretation (example calculations and threshold guidance: less than 2 implies more overlap, 2 or more implies less overlap).

Students compare two numerical distributions on dot plots (Opal's and Randall's grades; fiction vs. nonfiction weeks on best-seller lists) and compute means and mean absolute deviations. The materials instruct students to divide the difference of the two means by the larger mean absolute deviation (answers shown as 1.4 and 1) and then judge whether one distribution will likely produce larger values. Students are also asked to inspect the dot plots for outliers and to make an inference about which population is likely to have larger typical values.

The project requires students to organize data and create dot plots or histograms (Step 3) and to calculate measures of center (mean, median) and measures of variability including interquartile range and mean absolute deviation (Step 4). Students are asked to draw a box plot and label the five-number summary, and to answer analysis questions about the shape of the data, outliers, and what the range, IQR, and MAD tell them about variability (Step 5). The presentation must include the data's mean, median, mode, range, interquartile range, and mean absolute deviation and include analysis and inferences about the data.

Students calculate measures of center (mean, median) and measures of variability (range, IQR, MAD) and practice creating and interpreting box plots (Activities 1–4). In Variability Practice students compare two box plots (Class A vs Class B) and answer which class has more consistent scores, and another task asks students to compare two data sets with IQR = 2 and IQR = 10. A MAD scenario presents a mean and MAD (mean = 6, MAD = 0.8) and asks students to interpret whether the data are tightly clustered or spread out.

Students are asked to calculate measures of center (mean, median, mode) and measures of spread including mean absolute deviation (MAD) on multiple practice problems. Students compare distributions using box plots and IQR in activities that ask which group is more consistent (e.g., Activity 18 comparing Class A and Class B, and later Class X and Class Y). Several problems require computing MAD and IQR (Jumping Jacks, other datasets), providing practice with both centers and variability measures.

Students calculate measures of variability including mean absolute deviation (MAD) and interquartile range (IQR) and draw box plots (Activity 2). Students compare two classes by mean and MAD to judge which class has more consistent scores (Activity 2, question 6). Students also compute and compare measures of center (mean and median) and interpret the effect of outliers on the mean versus median (Activity 1).

Unit 8 asks students to compute mean, median, mode, range and mean absolute deviation (MAD) for data sets and to draw a box plot. Problems include "What does the MAD tell you about the spread of the data?" and a direct comparison: "Which class has more consistent scores? Explain. Class A: Mean = 78, MAD = 4; Class B: Mean = 78, MAD = 9." Students are also asked to find IQR and interpret box plots.