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. These characteristics of the problem drive the forecasting approaches.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Mark Raskino

AUGUST 30, 2017

For example in 2003, when I visited Zagreb in Croatia for the first time – they had mobile phone text based payment for car parking. He was talking about something we call the ‘compound uncertainty’ that must be navigated when we want to test and introduce a real breakthrough digital business idea. This is not a new observation.

Testing 53

Testing Experimentation Uncertainty Risk 53

Andrew White

APRIL 22, 2020

In this second phase executive leaders will need to make critical business decisions with even less data and with more uncertainty. This enthusiasm for the topic hearkens back to Erik Brynjolfsson’s popular opine from a paper in 2003 (Computing Productivity: Firm Level Evidence): we see productivity growth all around us; just not in the data.

Software 52

Software Measurement Uncertainty Marketing 52

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. References.

Statistics 27

Statistics Uncertainty Risk Marketing 27