Remove 2015 Remove Data mining Remove Reporting Remove Testing
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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics? Data analytics and data science are closely related.

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Misleading Statistics Examples – Discover The Potential For Misuse of Statistics & Data In The Digital Age

datapine

To make sure the reliability is high, there are various techniques to perform – the first of them being the control tests, which should have similar results when reproducing an experiment in similar conditions. 29, 2015, Republicans from the U.S. Chaffetz’s numbers via a comparison with Planned Parenthood’s own annual reports.

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Magnificent Mobile Website And App Analytics: Reports, Metrics, How-to!

Occam's Razor

Dive into Mobile Reporting and Analysis. Dive into Mobile Reporting and Analysis. So, use GTM, implement one container tag, turn on the standard GA tag, configure goals in GA admin, you are ready for a lot of mobile data analysis! Dive into Mobile Reporting and Analysis. What do you learn from this report?

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MLOps and the evolution of data science

IBM Big Data Hub

Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. These insights can help drive decisions in business, and advance the design and testing of applications.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

Another reason to use ramp-up is to test if a website's infrastructure can handle deploying a new arm to all of its users. The website wants to make sure they have the infrastructure to handle the feature while testing if engagement increases enough to justify the infrastructure. We offer two examples where this may be the case.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

Modeling live experiment data Data scientists at YouTube are rarely involved in the analysis of typical live traffic experiments. Multiparameter experiments, however, generate richer data than standard A/B tests, and automated t-tests alone are insufficient to analyze them well. Technical report, Google, 2012. [13]

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Using Empirical Bayes to approximate posteriors for large "black box" estimators

The Unofficial Google Data Science Blog

One way to check $f_theta$ is to gather test data and check whether the model fits the relationship between training and test data. This tests the model’s ability to distinguish what is common for each item between the two data sets (the underlying $theta$) and what is different (the draw from $f_theta$).

KDD 40