Remove 2001 Remove Measurement Remove Modeling Remove Statistics
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A history of tech adaptation for today’s changing business needs

CIO Business Intelligence

The company has been on a continuous journey to adapt its internal and external processes to new business needs and opportunities since 2001.” According to Mohammed, the results of this digital transformation journey are measurable and impressive. “Digital transformation is not a new concept for Ipsos,” says global CIO Humair Mohammed.

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To Balance or Not to Balance?

The Unofficial Google Data Science Blog

A naïve comparison of the exposed and unexposed groups would produce an overly optimistic measurement of the effect of the ad, since the exposed group has a higher baseline likelihood of purchasing a pickup truck. Identification We now discuss formally the statistical problem of causal inference. we drop the $i$ index.

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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

Meanwhile, many organizations also struggle with “late in the pipeline issues” on model deployment in production and related compliance. Their approach is to bombard “organoid” mini brains living in vats with potential cancer meds, to measure the meds’ relative effects. 2008 – Financial crisis : scientists flee Wall St.

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Reclaiming the stories that algorithms tell

O'Reilly on Data

Using the new scores, Apgar and her colleagues proved that many infants who initially seemed lifeless could be revived, with success or failure in each case measured by the difference between an Apgar score at one minute after birth, and a second score taken at five minutes.

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Estimating the prevalence of rare events — theory and practice

The Unofficial Google Data Science Blog

But importance sampling in statistics is a variance reduction technique to improve the inference of the rate of rare events, and it seems natural to apply it to our prevalence estimation problem. 2] Lawrence Brown, Tony Cai, Anirban DasGupta (2001). Statistical Science. Statistics in Biopharmaceutical Research, 2010. [4]

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