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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Taking measurements at parameter settings further from control parameter settings leads to a lower variance estimate of the slope of the line relating the metric to the parameter.

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Uncertainties: Statistical, Representational, Interventional

The Unofficial Google Data Science Blog

Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature. Representational uncertainty : the gap between the desired meaning of some measure and its actual meaning.

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What Is DataOps? Definition, Principles, and Benefits

Alation

However, there is a lot more to know about DataOps, as it has its own definition, principles, benefits, and applications in real-life companies today – which we will cover in this article! In DataOps, data analytics performance is primarily measured through insightful analytics, and accurate data, in robust frameworks.

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Glossary of Digital Terminology for Career Relevance

Rocket-Powered Data Science

Definitions of terminology frequently seen and used in discussions of emerging digital technologies. Examples: (1-3) All those applications shown in the definition of Machine Learning. (4) Example applications: (1) High-definition and 3D video. (2) Career Relevance. NOTE: This page is a WIP = Work In Progress.). Industry 4.0

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Measuring Incrementality: Controlled Experiments to the Rescue!

Occam's Razor

This: You understand all the environmental variables currently in play, you carefully choose more than one group of "like type" subjects, you expose them to a different mix of media, measure differences in outcomes, prove / disprove your hypothesis (DO FACEBOOK NOW!!!), Measuring Incrementality: Controlled Experiments to the Rescue!

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Experimentation and Testing: A Primer

Occam's Razor

This post is a primer on the delightful world of testing and experimentation (A/B, Multivariate, and a new term from me: Experience Testing). Experimentation and testing help us figure out we are wrong, quickly and repeatedly and if you think about it that is a great thing for our customers, and for our employers.

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Variance and significance in large-scale online services

The Unofficial Google Data Science Blog

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.