When should I use log transformation for outliers?
Log transformation is useful when you have positive skewness in your data, especially with outliers.
Can you explain how log transformation helps with skewed data?
It compresses the range of the data, reducing the impact of extreme values and making the distribution more normal.
Are there any situations where I shouldn't use log transformation?
Yes, if your data contains zero or negative values, log transformation isn't appropriate.
What are some alternatives to log transformation for handling outliers?
You could consider using winsorization, z-score normalization, or robust scaling as alternatives.
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