Cross Validated
2022-10-31 20:54 UTC
By Kevin
AI-113-20221031-social-media-56211fb5
Can I apply both winsorization and CUPED to my experiment results?
Our current experimentation platform currently has winsorization implemented to reduce "whale effects" on metrics like revenue and volume. We are also interested in applying CUPED to further reduce variances based on pre-experiment values. My question is: can I apply both and in what way would make the most sense? My analysis shows CUPED does indeed reduce the variances for revenue when compared to the non-winsorized values but they're still larger when compared to the winsorized variances.
Our current experimentation platform currently has winsorization implemented to reduce "whale effects" on metrics like revenue and volume. We are also interested in applying CUPED to further reduce variances based on pre-experiment values. My question is: can I apply both and in what way would make the most sense? My analysis shows CUPED does indeed reduce the variances for revenue when compared to the non-winsorized values but they're still larger when compared to the winsorized variances.
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Cross Validated
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