Data Science 101

JANUARY 15, 2020

Researchers/ scientists perform experiments to validate their hypothesis/ statements or to test a new product. Suppose we want to test the effectiveness of a new drug against a particular disease. Bias can cause a huge error in experimentation results so we need to avoid them. We randomly recruit subjects for that.

Experimentation 96

Experimentation Statistics Measurement Testing 96

The Unofficial Google Data Science Blog

JULY 22, 2020

For example, imagine a fantasy football site is considering displaying advanced player statistics. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown.

Experimentation 95

Experimentation Statistics Testing Strategy 95

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

1]" Statistics, as a discipline, was largely developed in a small data world. Yet when we use these tools to explore data and look for anomalies or interesting features, we are implicitly formulating and testing hypotheses after we have observed the outcomes. We must correct for multiple hypothesis tests.

Experimentation 61

Experimentation Testing Statistics Metrics 61

Occam's Razor

MARCH 23, 2010

Part of it is fueled by a vocal minority genuinely upset that 10 years on we are still not a statistically powered bunch doing complicated analysis that is shifting paradigms. Usually at least a test. Meanwhile see if you can convince your HiPPO to run a small test while you look for a case study (and a job). ]. Likely not.

Analytics 118

Analytics Consulting Metrics Experimentation 118