Remove 2007 Remove Experimentation Remove Modeling 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. Figure 2: Spreading measurements out makes estimates of model (slope of line) more accurate. And sometimes even if it is not[1].)

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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

Key To Your Digital Success: Web Analytics Measurement Model. Web Data Quality: A 6 Step Process To Evolve Your Mental Model. The Awesome Power of Visualization 2 -> Death and Taxes 2007. Build A Great Web Experimentation & Testing Program. Experimentation and Testing: A Primer. What's The Fix?

KPI 124
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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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Measuring Incrementality: Controlled Experiments to the Rescue!

Occam's Razor

How do you get over the frustration of having done attribution modeling and realizing that it is not even remotely the solution to your challenge of using multiple media channels? You need people with deep skills in Scientific Method , Design of Experiments , and Statistical Analysis. ask for a raise. It is that simple.

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

Occam's Razor

Let's listen in as Alistair discusses the lean analytics model… The Lean Analytics Cycle is a simple, four-step process that shows you how to improve a part of your business. Another way to find the metric you want to change is to look at your business model. The business model also tells you what the metric should be.

Metrics 156
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Estimating causal effects using geo experiments

The Unofficial Google Data Science Blog

A geo experiment is an experiment where the experimental units are defined by geographic regions. Statistical power is traditionally given in terms of a probability function, but often a more intuitive way of describing power is by stating the expected precision of our estimates. They are non-overlapping geo-targetable regions.