Remove 2011 Remove Experimentation Remove Metrics Remove Statistics
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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

To win in business you need to follow this process: Metrics > Hypothesis > Experiment > Act. We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. That metric is tied to a KPI.

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. This means it is possible to specify exactly in which geos an ad campaign will be served – and to observe the ad spend and the response metric at the geo level. They are non-overlapping geo-targetable regions. by turning campaigns off).

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Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

Although it’s not perfect, [Note: These are statistical approximations, of course!] We need to take a brief break from natural language-specific content here to introduce a metric that will come in handy in the next section of the chapter, when we will evaluate the performance of deep learning NLP models. Note: Maas, A., Example 11.6

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Unintentional data

The Unofficial Google Data Science Blog

1]" Statistics, as a discipline, was largely developed in a small data world. With more features come more potential post hoc hypotheses about what is driving metrics of interest, and more opportunity for exploratory analysis. Data was expensive to gather, and therefore decisions to collect data were generally well-considered.