Interquartile range (IQR)

Definition

Interquartile Range (IQR) measures the spread of the middle 50% of data points in a dataset. It is calculated by subtracting the first quartile (Q1) from the third quartile (Q3).

5 Must Know Facts For Your Next Test

1. The IQR is resistant to outliers and provides a better measure of spread for skewed distributions.
2. In finance, IQR helps analysts understand the variability in financial data such as stock prices or returns.
3. A larger IQR indicates greater dispersion within the middle 50% of data, while a smaller IQR suggests less variability.
4. To calculate IQR, you first need to arrange your data in ascending order and then find Q1 and Q3.
5. IQR is often used in box plots to visually represent data distribution and identify potential outliers.

Review Questions

• What does the interquartile range (IQR) measure?
• How do you calculate the interquartile range in a dataset?
• Why is IQR considered more robust against outliers compared to other measures of spread?

Related terms

Quartiles: Quartiles divide a ranked dataset into four equal parts.

Outliers: Data points that are significantly different from other observations and can distort statistical analyses.

Box Plot: A graphical representation that uses quartiles to show the distribution of a dataset along with its median and potential outliers.