Practice calculating the Mean Absolute Deviation (MAD) of a data set step-by-step—starting from the mean, to absolute deviations, and finally to the MAD value.
Help your 7th grade students build a deep understanding of Mean Absolute Deviation (MAD) with this interactive and auto-graded worksheet. Designed to align with Common Core Standard 7.SP.B.3, this hands-on activity walks students through each step of calculating MAD, reinforcing key statistical concepts while offering instant feedback.
Students will:
Features of this worksheet:
This worksheet is part of our interactive math series and is perfect for building data literacy while keeping students engaged. Teachers can monitor progress in real time and quickly identify where students may need extra support.
At the end of this worksheet, students will be able to calculate and interpret the Mean Absolute Deviation (MAD) for a given dataset.
If randomization is enabled when assigning to the classroom, each student will get different set of numbers to find the MAD. This prevents copying of answers and helps individualized learning.
💡 Tip: When assigning this activity to your classroom, you can optionally enable randomization to give each student a unique version of the problems. When you re-assign the same worksheet, each student will get a new set of questions, helping them master the content through repeated practice.
Understand that a set of data collected to answer a statistical question has a distribution which can be described by its center, spread, and overall shape.
All 6.SP.A.2 activities →Recognize that a measure of center for a numerical data set summarizes all of its values with a single number, while a measure of variation describes how its values vary with a single number.
All 6.SP.A.3 activities →Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the centers by expressing it as a multiple of a measure of variability. *For example, the mean height of players on the basketball team is 10 cm greater than the mean height of players on the soccer team, about twice the variability (mean absolute deviation) on either team; on a dot plot, the separation between the two distributions of heights is noticeable*.
All 7.SP.B.3 activities →Use measures of center and measures of variability for numerical data from random samples to draw informal comparative inferences about two populations. *For example, decide whether the words in a chapter of a seventh-grade science book are generally longer than the words in a chapter of a fourth-grade science book*.
All 7.SP.B.4 activities →Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.
All 8.SP.A.1 activities →More interactive, auto-graded activities on the same standards and topics.
Students compare the sleep patterns of 7th and 8th graders using real-world data. They calculate mean, median, range, and IQR, then interpret histograms and make informal inferences about group differences. This worksheet supports randomization, so each student may receive different sleep data.
Students analyze test score data from two schools — one using tablets, the other using textbooks — to calculate mean, median, range, and IQR. They compare the distributions using numerical measures and histograms to draw conclusions about student performance.
Students will analyze dot plots representing real-world data, such as the ages of students participating in a school carnival. They will answer questions based on these plots. Each student will receive three unique sets of data and questions, encouraging individual analysis and critical thinking.
Students will analyze four types of graphs: a scatter plot, a histogram, a bar chart, and a line chart. Their task is to interpret the data presented in each graph and answer specific questions related to the information.
Students put a data set in order, split it into halves, and find Q1, Q3 and the interquartile range one guided step at a time. Feedback names the exact mistake, and a number line shades the middle half once they get it right. 8 auto-graded questions, randomized for every student and aligned to 6.SP.B.5c. Assign it for a 20 to 30 minute practice block.
Students will analyze five different data sets, each representing a real-life scenario such as weekly attendance or pages read by students. Their task is to calculate the mean, median, mode, range, and interquartile range for each data set, helping them develop essential skills in statistical analysis.
