What is the IQR method for detecting outliers?
The IQR method, or Interquartile Range method, is a statistical technique used to identify outliers in a dataset. It calculates the range between the first quartile (Q1) and the third quartile (Q3) and identifies values that fall below Q1 - 1.5 * IQR or above Q3 + 1.5 * IQR as outliers.
How do I calculate the IQR?
To calculate the IQR, first, find Q1 (the 25th percentile) and Q3 (the 75th percentile) of your data. Then, subtract Q1 from Q3: IQR = Q3 - Q1.
Can you give me an example of using the IQR method?
Sure! Suppose you have the data set: [1, 2, 3, 4, 5, 100]. Q1 is 2.5, Q3 is 4.5, so IQR = 4.5 - 2.5 = 2. If we calculate the outlier thresholds, any value below 0 or above 6 will be considered an outlier. In this case, 100 is an outlier.
What are some limitations of the IQR method?
The IQR method assumes a symmetric distribution and may not perform well with skewed data. It also may not detect outliers in small datasets effectively.
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