Remove 2007 Remove Experimentation Remove Optimization Remove Statistics
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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

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. In isolation, the $x_1$-system is optimal: changing $x_1$ and leaving the $x_2$ at 0 will decrease system performance.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

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.

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To Balance or Not to Balance?

The Unofficial Google Data Science Blog

In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. Identification We now discuss formally the statistical problem of causal inference. We start by describing the problem using standard statistical notation.

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Knowledge

Occam's Razor

The Awesome Power of Visualization 2 -> Death and Taxes 2007. Build A Great Web Experimentation & Testing Program. Experimentation and Testing: A Primer. Tip #9: Leverage Statistical Control Limits. Tip#1: Statistical Significance. Search Engine Optimization (SEO) Metrics & Analytics.

KPI 124
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Measuring Incrementality: Controlled Experiments to the Rescue!

Occam's Razor

We have to do Search Engine Optimization. You need people with deep skills in Scientific Method , Design of Experiments , and Statistical Analysis. The team did the normal modeling to ensure that the results were statistically significant (large enough sample set, sufficient number of conversions in each variation). *

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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. You're choosing only one metric because you want to optimize it. Remember that the raw number is not the only important part, we would also measure statistical significance. But it is not routine.

Metrics 156