📝 Practice Worksheets
🔑 Key Concepts
- The interquartile range measures the spread of the middle 50% of a data set.
- IQR is calculated using \( IQR = Q_3 - Q_1 \).
- To find IQR correctly, the data must first be ordered from least to greatest.
- Sometimes the median, \( Q_1 \), or \( Q_3 \) is an actual middle number, and sometimes it must be found by averaging two middle numbers.
- Whether you average or not depends on how many values are in the full data set or in each half of the data.
💡 Main Idea
This lesson focuses on finding the interquartile range of a data set by carefully identifying \( Q_1 \) and \( Q_3 \). A major idea in this video is that students must pay close attention to whether there is one middle number or two middle numbers when finding the median of the full data set or the median of either half. In some problems, the middle value is already present in the data. In others, the correct quartile must be found by averaging the two middle numbers. Once \( Q_1 \) and \( Q_3 \) are identified, the IQR is found by subtracting \( Q_1 \) from \( Q_3 \).
📚 What You Should Already Know
Before watching this lesson, students should know how to order numbers from least to greatest and how to find the median of a data set. They should also understand that when there is no single middle number, the median must be found by averaging the two middle values. That same idea is important when finding \( Q_1 \) and \( Q_3 \), since each half of the data may or may not have a physical middle number.
🚀 What Comes Next
After this lesson, students can apply IQR to box plots, compare multiple data sets, and describe variability more precisely. This also prepares students to interpret how tightly clustered or spread out the middle half of a data set is when reading statistical graphs.
🧩 Embed This Video in Your LMS
Teachers can embed this YouTube video directly into Canvas, Google Classroom, Schoology, or another learning platform. Click below to show the embed code.