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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

Crucially, it takes into account the uncertainty inherent in our experiments. Multiparameter experiments, however, generate richer data than standard A/B tests, and automated t-tests alone are insufficient to analyze them well. In this section we’ll discuss how we approach these two kinds of uncertainty with QCQP.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

One reason to do ramp-up is to mitigate the risk of never before seen arms. 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. For example, imagine a fantasy football site is considering displaying advanced player statistics.

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The trinity of errors in applying confidence intervals: An exploration using Statsmodels

O'Reilly on Data

Because of this trifecta of errors, we need dynamic models that quantify the uncertainty inherent in our financial estimates and predictions. Practitioners in all social sciences, especially financial economics, use confidence intervals to quantify the uncertainty in their estimates and predictions. and an error term ??

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Estimating causal effects using geo experiments

The Unofficial Google Data Science Blog

Similarly, we could test the effectiveness of a search ad compared to showing only organic search results. Structure of a geo experiment A typical geo experiment consists of two distinct time periods: pretest and test. After the test period finishes, the campaigns in the treatment group are reset to their original configurations.

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Misleading Statistics Examples – Discover The Potential For Misuse of Statistics & Data In The Digital Age

datapine

With the rise of advanced technology and globalized operations, statistical analyses grant businesses an insight into solving the extreme uncertainties of the market. Drinking tea increases diabetes by 50%, and baldness raises the cardiovascular disease risk up to 70%! So, can statistics be manipulated? They sure can. Do numbers lie?