2003, Measurement, Testing and Uncertainty

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

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

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. For example, we may prefer one model to generate a range, but use a second scenario-based model to “stress test” the range.

Forecasting

Forecasting Data Science Statistics Uncertainty

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

O'Reilly on Data

DECEMBER 9, 2019

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.

Statistics

Statistics Uncertainty Risk Marketing

Data Leaders Brief

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

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

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