Occam's Razor

APRIL 8, 2013

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Testing out a new feature. Identify, hypothesize, test, react. But at the same time, they had to have a real test of an actual feature. You don’t need a beautiful beast to go out and test.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Occam's Razor

JUNE 4, 2018

I mean developing and inserting a subtle collection of gentle nudges that can help increase the conversion rate by a statistically significant amount. Checkout the Kimbao Sauvignon Blanc you can see sales and would buy it again rates since 2011. Such is the case with A/B testing. I don’t mean: BUY IT NOW OR ELSE! Add to Basket!

Strategy 124

Strategy Cost-Benefit Testing Sales 124

The Unofficial Google Data Science Blog

MAY 31, 2016

Similarly, we could test the effectiveness of a search ad compared to showing only organic search results. A geo experiment is an experiment where the experimental units are defined by geographic regions. Structure of a geo experiment A typical geo experiment consists of two distinct time periods: pretest and test.

Advertising 42

Advertising Testing Sales Statistics 42

Occam's Razor

SEPTEMBER 13, 2016

If you are curious, here is a April 2011 post: The Difference Between Web Reporting And Web Analysis. Hypothesis development and design of experimentation. Ok, maybe statistical modeling smells like an analytical skill. If these 50 pass the sniff test, send the survey. Pattern recognition and understanding trends.

Modeling 127

Modeling Reporting Strategy Consulting 127

Domino Data Lab

AUGUST 22, 2019

Although it’s not perfect, [Note: These are statistical approximations, of course!] Note: A test set of 19,500 such analogies was developed by Tomas Mikolov and his colleagues in their 2013 word2vec paper. This test set is available at download.tensorflow.org/data/questions-words.txt.]. Note that the final test word in Table 11.2—ma’am—is

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

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