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Resource ID: #805
Subject: 109
Source: 2198When correlation is causation
Affiliation: Independent journalist
Date: 2016

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Description

Is red meat bad for your health? What's a triple-blind clinical trial? Are the Finnish really that great at mathematics? What's so significant about statistical significance? During the first half of this workshop, you'll get acquainted with concepts like confounding, selection bias, Simpson's paradox, randomization and statistical power. In the second half, it's up to you: judge your way through a series of small case studies and practice what you've learned. It's not enough to say that correlation does not imply causation. Learn exactly what stands in the way of drawing truthful conclusions from data, how to recognize great science and how to spot the flaws that invalidate statistical conclusions.

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