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Detecting Outliers in Data
Formula
Outliers are data points that differ significantly from other observations. They can result from measurement errors, data entry mistakes, or genuine extreme values. Identifying outliers is an important step in data cleaning and analysis.
The IQR method defines outliers as values below Q1 - 1.5*IQR or above Q3 + 1.5*IQR. The Z-score method flags values with |Z| > 3 as outliers.
Common use cases:
- Data cleaning before statistical analysis
- Fraud detection in financial data
- Quality control in manufacturing
Frequently Asked Questions
Dr. David Park
Applied Mathematician, PhD Mathematics
David holds a PhD in Applied Mathematics from MIT. He has published research on numerical methods and computational algorithms used in engineering and scientific calculators.
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