Remove Finance Remove Measurement Remove Statistics Remove Uncertainty
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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.

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Humans-in-the-loop forecasting: integrating data science and business planning

The Unofficial Google Data Science Blog

This classification is based on the purpose, horizon, update frequency and uncertainty of the forecast. With those stakes and the long forecast horizon, we do not rely on a single statistical model based on historical trends. These characteristics of the problem drive the forecasting approaches.

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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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Tackling changed requirements with comprehensive modernization

BI-Survey

Overnight, the impact of uncertainty, dynamics and complexity on markets could no longer be ignored. Local events in an increasingly interconnected economy and uncertainties such as the climate crisis will continue to create high volatility and even chaos. The COVID-19 pandemic caught most companies unprepared. BARC Recommendations.

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The trinity of errors in applying confidence intervals: An exploration using Statsmodels

O'Reilly on Data

Because of this trifecta of errors, we need dynamic models that quantify the uncertainty inherent in our financial estimates and predictions. Practitioners in all social sciences, especially financial economics, use confidence intervals to quantify the uncertainty in their estimates and predictions.

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LSOS experiments: how I learned to stop worrying and love the variability

The Unofficial Google Data Science Blog

In this post we explore why some standard statistical techniques to reduce variance are often ineffective in this “data-rich, information-poor” realm. Despite a very large number of experimental units, the experiments conducted by LSOS cannot presume statistical significance of all effects they deem practically significant.