CIO Business Intelligence

NOVEMBER 3, 2023

The stages of burnout Developing over time, burnout builds in distinct stages that lead employees down a path of low motivation, cynicism, and eventually depersonalization, according to Yerbo’s The State of Burnout in Tech report, which points to 2005 research by Salanova and Schaufeli on the subject.

IT 131

IT Reporting Uncertainty Cost-Benefit 131

Peter James Thomas

JUNE 20, 2019

Of course it can be argued that you can use statistics (and Google Trends in particular) to prove anything [1] , but I found the above figures striking. Computerworld – Gartner: Customer-service outsourcing often fails , Scarlet Pruitt, March 2005. King was a wise King, but now he was gripped with uncertainty.

Cost-Benefit 55

Cost-Benefit Data Warehouse Consulting Data Science 55

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. They learned about a lot of process that requires that you get rid of uncertainty. They’re being told they have to embrace uncertainty.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

The Unofficial Google Data Science Blog

JULY 18, 2023

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. But for more complicated metrics like xRR, our preference is to bootstrap when measuring uncertainty.

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

The Unofficial Google Data Science Blog

MARCH 31, 2016

We often use statistical models to summarize the variation in our data, and random effects models are well suited for this — they are a form of ANOVA after all. In the context of prediction problems, another benefit is that the models produce an estimate of the uncertainty in their predictions: the predictive posterior distribution.

Modeling 40

Modeling Statistics Advertising Testing 40