O'Reilly on Data

JANUARY 22, 2019

They trade the markets using quantitative models based on non-financial theories such as information theory, data science, and machine learning. Whether financial models are based on academic theories or empirical data mining strategies, they are all subject to the trinity of modeling errors explained below. Not even close.

Modeling 134

Modeling Finance Uncertainty Data mining 134

The Unofficial Google Data Science Blog

APRIL 23, 2024

Crucially, it takes into account the uncertainty inherent in our experiments. Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. It is a big picture approach, worthy of your consideration.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

The Unofficial Google Data Science Blog

JULY 22, 2020

For this reason we don’t report uncertainty measures or statistical significance in the results of the simulation. From a Bayesian perspective, one can combine joint posterior samples for $E[Y_i | T_i=t, E_i=j]$ and $P(E_i=j)$, which provides a measure of uncertainty around the estimate. 2015): 37-45. [3] 2] Scott, Steven L.

Experimentation 95

Experimentation Statistics Testing Strategy 95

datapine

DECEMBER 28, 2021

With the rise of advanced technology and globalized operations, statistical analyses grant businesses an insight into solving the extreme uncertainties of the market. While certain topics listed here are likely to stir emotion depending on one’s point of view, their inclusion is for data demonstration purposes only. 3) Data fishing.

Statistics 363

Statistics Advertising Visualization Data mining 363