Once outliers are detected, several strategies can be adopted:
1. Exclusion: Removing outliers from the dataset, though this approach should be taken with caution as it may lead to loss of valuable information. 2. Transformation: Applying transformations (e.g., log transformation) to reduce the impact of outliers. 3. Robust Statistical Methods: Using statistical methods that are less affected by outliers, such as non-parametric tests. 4. Further Investigation: Investigating the reasons behind the outliers to determine if they represent valuable information or errors.
