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Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. We describe experiment designs which have proven effective for us and discuss the subtleties of trying to generalize the results via modeling.

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Key To Your Digital Success: Web Analytics Measurement Model. Slay The Analytics Data Quality Dragon & Win Your HiPPO's Love! Web Data Quality: A 6 Step Process To Evolve Your Mental Model. The Ultimate Web Analytics Data Reconciliation Checklist. Data Mining And Predictive Analytics On Web Data Works?

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

Another reason to use ramp-up is to test if a website's infrastructure can handle deploying a new arm to all of its users. The website wants to make sure they have the infrastructure to handle the feature while testing if engagement increases enough to justify the infrastructure. We offer two examples where this may be the case.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. That is true generally, not just in these experiments — spreading measurements out is generally better, if the straight-line model is a priori correct.

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

datapine

To make sure the reliability is high, there are various techniques to perform – the first of them being the control tests, which should have similar results when reproducing an experiment in similar conditions. In 2007, Colgate was ordered by the Advertising Standards Authority (ASA) of the U.K. 3) Data fishing.