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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
Maria Gonzalez
Registered Dietitian, RD, MPH
Maria is a Registered Dietitian with a Master's in Public Health. She focuses on evidence-based nutrition assessment tools including BMI, calorie calculations, and body composition analysis.
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