What are outliers, and how do you identify them?

**Outliers are data points that are significantly different from the rest of the data. They can be unusually high or unusually low values.**

Dataset:

10, 12, 15, 18, 20, 22, 100

Here, 100 is an outlier because it is much larger than the other values.

Why are Outliers Important?

• Q1 (25th percentile)
• Q3 (75th percentile)
• IQR = Q3 − Q1

Values are considered outliers if they are:

• Less than Q1 − 1.5 × IQR
• Greater than Q3 + 1.5 × IQR

2. Z-Score Method

The Z-score measures how far a value is from the mean.

• If |Z| > 3, the value is often considered an outlier.

3. Box Plot

A box plot visually shows:

• Median
• Quartiles
• Potential outliers as points outside the whiskers

4. Scatter Plot

For large datasets, scatter plots help identify unusual observations that differ from the overall pattern.

“Outliers are observations that differ significantly from other data points. They can result from errors or represent genuine unusual events. Common methods to identify outliers include the IQR method, Z-score analysis, box plots, and scatter plots.”