Why are outliers important in data science?
An example of an AI chatbot conversation about the significance of outliers in data analysis.
Why are outliers important in data science?
Outliers can provide valuable insights, indicating anomalies or unique cases that may affect analysis.
Can you give an example of an outlier affecting a dataset?
Sure! In a dataset of people's heights, a height of 7 feet could be an outlier, affecting average calculations.
How do we handle outliers in data analysis?
Outliers can be handled by removing them, transforming data, or using robust statistical methods.
What tools can help identify outliers?
Tools like box plots, scatter plots, and statistical tests like Z-scores can help identify outliers.
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