Data mining Experimentation Statistics Uncertainty 
CIO Business Intelligence
JUNE 28, 2023
These circumstances have induced uncertainty across our entire business value chain,” says Venkat Gopalan, chief digital, data and technology officer, Belcorp. “As The R&D laboratories produced large volumes of unstructured data, which were stored in various formats, making it difficult to access and trace.
The Unofficial Google Data Science Blog
APRIL 23, 2024
If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. Crucially, it takes into account the uncertainty inherent in our experiments. Why experiment with several parameters concurrently?
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The Unofficial Google Data Science Blog
JANUARY 14, 2016
by AMIR NAJMI Running live experiments on large-scale online services (LSOS) is an important aspect of data science. Because individual observations have so little information, statistical significance remains important to assess. We must therefore maintain statistical rigor in quantifying experimental uncertainty.
The Unofficial Google Data Science Blog
JULY 22, 2020
For example, imagine a fantasy football site is considering displaying advanced player statistics. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. One reason to do ramp-up is to mitigate the risk of never before seen arms.
The Unofficial Google Data Science Blog
FEBRUARY 29, 2016
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.
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