What is the impact of outlier detection on data quality?

What is the impact of outlier detection on data quality?

Outlier detection helps identify and remove anomalies in data, improving its accuracy and reliability.

Can you explain how outliers affect data analysis?

Outliers can skew results, leading to misleading conclusions and affecting statistical analyses.

What methods are commonly used for outlier detection?

Common methods include Z-score analysis, IQR method, and machine learning techniques like isolation forests.

How can I implement outlier detection in my dataset?

You can use libraries like Pandas in Python to apply statistical methods or machine learning algorithms for detection.

Are there any risks associated with removing outliers?

Yes, removing outliers can lead to loss of valuable information, so it's important to analyze them carefully.