2016 Measurement Testing Uncertainty 
Data Science and Beyond
JULY 28, 2017
As I haven’t heard anything from Automattic at that stage, it seemed unwise to reject a good offer, so I started working full-time with Car Next Door in January 2016. I finally heard back from Automattic in February 2016 (four months after my initial application and a month into my employment with Car Next Door).
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.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
O'Reilly on Data
DECEMBER 9, 2019
Because of this trifecta of errors, we need dynamic models that quantify the uncertainty inherent in our financial estimates and predictions. Practitioners in all social sciences, especially financial economics, use confidence intervals to quantify the uncertainty in their estimates and predictions.
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. These controlling measures are essential and should be part of any experiment or survey – unfortunately, that isn’t always the case. degrees Fahrenheit.
O'Reilly on Data
JUNE 16, 2020
But when making a decision under uncertainty about the future, two things dictate the outcome: (1) the quality of the decision and (2) chance. This essay is about how to take a more principled approach to making decisions under uncertainty and aims to provide certain conceptual and cognitive tools for how to do so, not what decisions to make.
Expert insights. Personalized for you.
81 
Let's personalize your content