Remove 2017 Remove Metrics Remove Statistics Remove Uncertainty
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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., Crucially, it takes into account the uncertainty inherent in our experiments. Here, $X$ is a vector of tuning parameters that control the system's operating characteristics (e.g.

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Measuring Validity and Reliability of Human Ratings

The Unofficial Google Data Science Blog

Once we’ve answered that, we will then define and use metrics to understand the quality of human-labeled data, along with a measurement framework that we call Cross-replication Reliability or xRR. We will follow the example of Janson and Olsson , and start from this generalized definition of the metric, which they call iota.

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Fact-based Decision-making

Peter James Thomas

Pertinence and fidelity of metrics developed from Data. Metrics are seldom reliant on just one data element, but are often rather combinations. There are often compromises to be made in defining metrics. Integrity of statistical estimates based on Data. For example: Is this a good way to define New Business Growth?

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