outlier_detection_and_treatment.md

Outlier Detection & Treatment

• Tutorial Notebook
• Reference:
  • Outlier Detection and Treatment: Z-score, IQR, and Robust Methods

Outlier Impact

• Skewed Statistics: Means and standard deviations can be distorted.
• Misleading Visualizations: Outliers affect the readability of charts and graphs.
• Model Performance Issues: In machine learning, outliers can cause models to misfit data, leading to poor generalization.

Outlier Detection Techniques

• There are several ways to detect outliers, each with its own strengths and limitations.
  • Z-score method
  • IQR (Interquartile Range) method
  • Robust methods

Method	Best For	Limitations	Suitable Distributions
Z-score	Normally distributed data	Sensitive to extreme values	Normal
IQR	Skewed distributions	May not work well for small datasets	Skewed or normal
MAD	Skewed or non-normal data	Interpretation can be complex	Highly skewed