Alation

OCTOBER 12, 2022

Companies collect and analyze vast amounts of data to make informed business decisions. From product development to customer satisfaction, nearly every aspect of a business uses data and analytics to measure success and define strategies. So what are the key differences, and what should data users know about them?

Statistics 52

Statistics Sales Testing Marketing 52

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., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Occam's Razor

DECEMBER 12, 2011

We have access to more data than God wants anyone to have. Thus it is not surprising that we feel overwhelmed, and rather than being data driven we just get paralyzed. In fact a data driven life is sexiest digital life you can imagine. A/B & Multivariate tests are a good option. Let's do this!

Metrics 151

Metrics Key Performance Indicator Measurement Optimization 151

datapine

DECEMBER 28, 2021

Statistics are infamous for their ability and potential to exist as misleading and bad data. Exclusive Bonus Content: Download Our Free Data Integrity Checklist. Get our free checklist on ensuring data collection and analysis integrity! To get this journey started let’s look at the misleading statistics definition.

Statistics 363

Statistics Advertising Visualization Data mining 363