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Calculate the IQR (Q3 - Q1) and identify outliers using the 1.5×IQR rule.
The Interquartile Range measures the spread of the middle 50% of your data. It's resistant to outliers, making it a robust measure of variability.
Unlike methods using mean/std dev, the IQR method isn't affected by the very outliers it's trying to detect, making it more reliable.
The 1.5×IQR rule was proposed by John Tukey. For normal distributions, about 99.3% of data falls within this range, so values outside are considered unusual.
Only remove outliers if they represent errors or are not relevant to your analysis. Many outliers are valid data points that provide important information.