Interquartile Range (IQR) Examples in Statistics
Start with the recap, study the fully worked examples, then use the practice problems to check your understanding of Interquartile Range (IQR).
This page combines explanation, solved examples, and follow-up practice so you can move from recognition to confident problem-solving in Statistics.
Concept Recap
The interquartile range (IQR) is the range of the middle 50% of data, calculated as . It measures spread while ignoring the top and bottom 25% of values, making it resistant to outliers.
IQR focuses on where most of the data lives, ignoring the extremes. If regular range is how far the outliers stretched, IQR is how wide the main crowd is. More resistant to outliers than range.
Read the full concept explanation โHow to Use These Examples
- Read the first worked example with the solution open so the structure is clear.
- Try the practice problems before revealing each solution.
- Use the related concepts and background knowledge badges if you feel stuck.
What to Focus On
Core idea: Interquartile Range (IQR) asks how tightly or loosely the values sit around the data set, not just where the middle is.
Common stuck point: Students often know a procedure related to interquartile range (iqr) but skip the recognition step: Do I need to describe how far the data values extend or vary, rather than where the middle is? That leads to a calculation or graph that looks reasonable but answers a different question.
Sense of Study hint: Ask: Do I need to describe how far the data values extend or vary, rather than where the middle is?
Worked Examples
Example 1
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Try these problems on your own first, then open the solution to compare your method.
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Background Knowledge
These ideas may be useful before you work through the harder examples.