The Unofficial Google Data Science Blog

APRIL 23, 2024

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. This blog post discusses such a comprehensive approach that is used at Youtube. Indeed, such an approach is tractable and often used.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

The Unofficial Google Data Science Blog

APRIL 17, 2017

Quantification of forecast uncertainty via simulation-based prediction intervals. Facebook in a recent blog post unveiled Prophet , which is also a regression-based forecasting tool. Prediction Intervals A statistical forecasting system should not lack uncertainty quantification. Accessed on 20 March 2017.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

The Unofficial Google Data Science Blog

JULY 22, 2020

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.

Experimentation 95

Experimentation Statistics Testing Strategy 95

The Unofficial Google Data Science Blog

JULY 18, 2023

That’s the focus of this blog post. Editor's note : The relationship between reliability and validity are somewhat analogous to that between the notions of statistical uncertainty and representational uncertainty introduced in an earlier post. To help ground these terms, imagine you have a bathroom scale.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

The Unofficial Google Data Science Blog

JULY 11, 2017

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. They may contain parameters in the statistical sense, but often they simply contain strategically placed 0's and 1's indicating which bits of $alpha_t$ are relevant for a particular computation. by STEVEN L.

Forecasting 64

Forecasting Statistics Modeling Software 64

O'Reilly on Data

DECEMBER 9, 2019

Recall from my previous blog post that all financial models are at the mercy of the Trinity of Errors , namely: errors in model specifications, errors in model parameter estimates, and errors resulting from the failure of a model to adapt to structural changes in its environment. The interval [-a, a] is called a 90% confidence interval.

Statistics 27

Statistics Uncertainty Risk Marketing 27

Peter James Thomas

AUGUST 12, 2018

This piece was prompted by both Olaf’s question and a recent article by my friend Neil Raden on his Silicon Angle blog, Performance management: Can you really manage what you measure? However – as is often the case with issues I deal with on this blog – fact-based decision-making is easier to say than it is to achieve.

Metrics 49

Metrics Statistics Data Quality Measurement 49