CIO Business Intelligence

NOVEMBER 29, 2023

When CEO Plinio Ayala joined Per Scholas in 2003, he noticed there weren’t enough skilled technicians to fix the hardware the organization collected. It was just talking about how computers work and the theory of code and the theory of statistical analysis and how best to write your code,” says Wilson.

IT 96

IT Software Technology Cost-Benefit 96

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

With those stakes and the long forecast horizon, we do not rely on a single statistical model based on historical trends. It provides the occasion for deeper exploration of which inputs that can be influenced and which risks can be proactively managed. The alternative we use is the forecast triangulation framework described above.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

bridgei2i

MAY 26, 2020

You know, their distribution channels, especially in growth in emerging markets, are severely strained economically because of their size. So, a lot of even these companies will have to re-engineer their analytics to reflect this new market reality. Anushruti: Right. Anushruti: Perfect. Love the simile, by the way.

Enterprise 131

Enterprise Management Forecasting Manufacturing 131

O'Reilly on Data

DECEMBER 9, 2019

We develop an ordinary least squares (OLS) linear regression model of equity returns using Statsmodels, a Python statistical package, to illustrate these three error types. CI theory was developed around 1937 by Jerzy Neyman, a mathematician and one of the principal architects of modern statistics.

Statistics 27

Statistics Uncertainty Risk Marketing 27