2011 Experimentation Modeling Reporting 
O'Reilly on Data
MAY 11, 2020
Not all models are created equal, however: they operate on different principles, and impact us as individuals and communities in different ways. To understand the menagerie of models that are fundamentally altering our individual and shared realities, we need to build a typology, a classification of their effects and impacts.
Domino Data Lab
AUGUST 6, 2021
Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.
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Occam's Razor
SEPTEMBER 13, 2016
If you are open to being challenged… then here are the short-stories inside this post… The World Needs Reporting Squirrels. Bonus #2: The Askers-Pukers Business Model. The World Needs Reporting Squirrels. If you are curious, here is a April 2011 post: The Difference Between Web Reporting And Web Analysis.
Occam's Razor
OCTOBER 21, 2013
In late 2011, Google announced an effort to make search behavior more secure. I've gone through the five stages in the Kubler-Ross model. The Multi-Channel Funnels folder in Google Analytics contains the Top Conversion Paths report. From there, jump to my personal favorite report in MCF, Assisted Conversions.
Occam's Razor
APRIL 8, 2013
We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. Another way to find the metric you want to change is to look at your business model. The business model also tells you what the metric should be.
The Unofficial Google Data Science Blog
OCTOBER 12, 2017
We data scientists now have access to tools that allow us to run a large numbers of experiments, and then to slice experimental populations by any combination of dimensions collected. Make experimentation cheap and understand the cost of bad decisions. This leads to the proliferation of post hoc hypotheses. Consider your loss function.
The Unofficial Google Data Science Blog
MAY 31, 2016
A geo experiment is an experiment where the experimental units are defined by geographic regions. The expected precision of our inferences can be computed by simulating possible experimental outcomes. The model regresses the outcomes $y_{1,i}$ on the incremental change in ad spend $delta_i$.
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