A data scientist notices that a dataset has a few values that are significantly higher than the others, skewing the results. What transformation technique might they consider to stabilize the variances?
- Log Transformation
- Min-Max Scaling
- Outlier Removal
- Standardization (Z-score normalization)
When dealing with a dataset containing significantly higher values that skew results, log transformation is a valuable technique. It compresses the range of values, making it easier to manage extreme values and stabilize variances. This is particularly useful in scenarios like financial data analysis or when dealing with data with a heavy right-skew.
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