Remove 2003 Remove Measurement Remove Risk Remove 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. A single model may also not shed light on the uncertainty range we actually face. These characteristics of the problem drive the forecasting approaches.

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What Will Drive Innovation in this Great Reset

Andrew White

Emergency measures are undertaken with little planning. In this second phase executive leaders will need to make critical business decisions with even less data and with more uncertainty. Many highly leveraged firms will be at risk; debt will be at record levels in public and private so anyone who has cash will be predatory.

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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.