Standardize dataset with high outliers Is there a better way to standardize a dataset with outliers than to normalized value (z-score) based on the mean and standard deviation? I am using the Excel STANDARDIZE function.
I have two datasets with huge outliers and I cannot remove them. Here is a summary of one of them.
Min. value: 0.29
Mean: 402,1
SD: 2222,89
Max. value: 23793
As can be noticed, I have a big range of values and all the lower values stay "hidden" by the highest ones.
What is the best way to standardize this dataset?


This data would be better visualised (and quite possibly analysed as well) with a transformation.
A log transformation is usually a good solution for right-skewed data such as this. If you have zeroes in there, a square root transformation should work well instead (it's best to avoid adding a constant before taking the log, even though that practice is common). And if you have negative values as well, try a cube root transformation.
EDIT: see Nick Cox's comment below for some helpful additional thoughts.
