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Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.
The result is that experimenters can’t afford to be sloppy about quantifying uncertainty. These typically result in smaller estimation uncertainty and tighter interval estimates. Variance reduction through conditioning Suppose, as an LSOS experimenter, you find that your key metric varies a lot by country and time of day.
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