2015 Experimentation Statistics Strategy 
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. It is also a sound strategy when experimenting with several parameters at the same time. And sometimes even if it is not[1].)
The Unofficial Google Data Science Blog
JULY 22, 2020
by ALEXANDER WAKIM Ramp-up and multi-armed bandits (MAB) are common strategies in online controlled experiments (OCE). These strategies involve changing assignment weights during an experiment. The first is a strategy called ramp-up and is advised by many experts in the field [1].
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The Unofficial Google Data Science Blog
JUNE 30, 2016
In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. Identification We now discuss formally the statistical problem of causal inference. We start by describing the problem using standard statistical notation.
Occam's Razor
JANUARY 9, 2012
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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. and an error term ??
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