2006 Reporting Statistics Uncertainty 
The Unofficial Google Data Science Blog
APRIL 17, 2017
Quantification of forecast uncertainty via simulation-based prediction intervals. Prediction Intervals A statistical forecasting system should not lack uncertainty quantification. We forecast this time series from the middle of 2006 through the end of the data, for a 30-month forecast horizon.
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. Crucially, it takes into account the uncertainty inherent in our experiments.
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Domino Data Lab
JULY 22, 2019
He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. If you look into the middle bucket, they have three things that they report in common. Tukey did this paper. It’s a great read.
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.
datapine
DECEMBER 28, 2021
1) What Is A Misleading Statistic? 2) Are Statistics Reliable? 3) Misleading Statistics Examples In Real Life. 4) How Can Statistics Be Misleading. 5) How To Avoid & Identify The Misuse Of Statistics? If all this is true, what is the problem with statistics? What Is A Misleading Statistic?
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