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

datapine

1) What Is A Misleading Statistic? 2) Are Statistics Reliable? 3) Misleading Statistics Examples In Real Life. 4) How Can Statistics Be Misleading. 5) How To Avoid & Identify The Misuse Of Statistics? If all this is true, what is the problem with statistics? What Is A Misleading Statistic?

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Decision-Making in a Time of Crisis

O'Reilly on Data

We know, statistically, that doubling down on an 11 is a good (and common) strategy in blackjack. The quality of the decision is based on known information and an informed risk assessment, while chance involves hidden information and the stochasticity of the world. Risk, Probability, Impact, and Decisions.

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Speed up queries with the cost-based optimizer in Amazon Athena

AWS Big Data

Starting today, the Athena SQL engine uses a cost-based optimizer (CBO), a new feature that uses table and column statistics stored in the AWS Glue Data Catalog as part of the table’s metadata. By using these statistics, CBO improves query run plans and boosts the performance of queries run in Athena.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. 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.

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What Are the Most Important Steps to Protect Your Organization’s Data?

Smart Data Collective

After a marginal increase in 2015, another steep rise happened in 2016 through 2017 before the volume decreased in 2018 and rose in 2019, and dropped again in 2020. They can use AI and data-driven cybersecurity technology to address these risks. One of the best solutions for data protection is advanced automated penetration testing.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. And we can keep repeating this approach, relying on intuition and luck.

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The 2015 Digital Marketing Rule Book. Change or Perish.

Occam's Razor

I've discovered that if we can just get them to imagine a better existence, undertake serious risks, experiment with new better ideas, and spend money executing them… they will ask for more robust measurement! AND you can control for risk! You can literally control for risk should everything blow up in your face.

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