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Variance and significance in large-scale online services

The Unofficial Google Data Science Blog

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.

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Performing Non-Compartmental Analysis with Julia and Pumas AI

Domino Data Lab

Having calculated AUC/AUMC, we can further derive a number of useful metrics like: Total clearance of the drug from plasma. Domino Lab supports both interactive and batch experimentation with all popular IDEs and notebooks (Jupyter, RStudio, SAS, Zeppelin, etc.). The area under the first moment curve would respectively be. cl_f = NCA.cl(pain_nca)

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LSOS experiments: how I learned to stop worrying and love the variability

The Unofficial Google Data Science Blog

In this post we explore why some standard statistical techniques to reduce variance are often ineffective in this “data-rich, information-poor” realm. Despite a very large number of experimental units, the experiments conducted by LSOS cannot presume statistical significance of all effects they deem practically significant.