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.
In this worksheet, students will work with five different data sets, each representing real-world scenarios such as weekly attendance of students in a class, the number of pages read in a week by different students, and other similar problems. The primary goal of this activity is to strengthen students’ understanding and application of key statistical measures by having them calculate the mean, median, mode, range, and interquartile range (IQR) for each data set.
Each student will receive a different set of numbers in each set of questions, helping to avoid the possibility of copying answers.
Teacher Tips:
This activity is designed to enhance students' ability to analyze and interpret data by applying fundamental statistical concepts, preparing them for more advanced topics in future lessons.
Key Features:
Students will be able to calculate and interpret measures of central tendency (mean, median, and mode) and measures of variability (range and interquartile range) from real-world data sets in order to summarize and describe data distributions.
If randomization is enabled, each student will get a different set of numbers to calculate the statistics. This helps prevent copying of answers and 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.
Summarize numerical data sets in relation to their context, such as by:
All 6.SP.B.5 activities →Reporting the number of observations.
All 6.SP.B.5a activities →Giving quantitative measures of center (median and/or mean) and variability (interquartile range and/or mean absolute deviation), as well as describing any overall pattern and any striking deviations from the overall pattern with reference to the context in which the data were gathered.
All 6.SP.B.5c 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 →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.
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.
