The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Crucially, it takes into account the uncertainty inherent in our experiments. Figure 2: Spreading measurements out makes estimates of model (slope of line) more accurate.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Occam's Razor

APRIL 8, 2013

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. First, you figure out what you want to improve; then you create an experiment; then you run the experiment; then you measure the results and decide what to do. Measure and decide what to do.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

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. 2] Scott, Steven L.

Experimentation 95

Experimentation Statistics Testing Strategy 95

The Unofficial Google Data Science Blog

APRIL 19, 2021

The numerical value of the signal became decoupled from the event it was measuring even as the ordinal value remained unchanged. bar{pi} (1 - bar{pi})$: This is the irreducible loss due to uncertainty. isn’t good enough: it optimizes the calibration term, but pays the price in sharpness. This shows why $Pr(mathrm{Spam}) = 0.1$

Modeling 122

Modeling IT Metrics Testing 122