The Statistical Power of Bayes’ Theorem [Infographic]

Nate Silver, known as the “King of Quants,” famously predicted the outcome of all 50 states in the 2012 presidential election. He correctly predicted the outcome of 49 of 50 states in the 2008 contest, and he even picked the NCAA tournament champions in 2012 and 2013—very impressive. He’s also the creator of Pecota, the most accurate baseball player performance forecasting system in the world. So, how does Silver do it? While the math behind his predictive system is unknown to the public, it is understood to be based on Bayes’ Theorem.

Bayes’ Theorem is a probability theory to measure the degree of belief that something will happen using conditional probabilities. The theorem was first developed in 1763, two years after Thomas Bayes’ death. Bayes’ Theorem can be used to predict outcomes in baseball—and the more variables you can add in, the more accurate the prediction will be.

To learn more about Bayes’ Theorem and how it can be applied to real-life situations, check out the infographic below!

Predicting Baseball: Demystifying Bayes' Theorem
Source: Predicting Baseball: Demystifying Bayes’ Theorem

The Statistical Power of Bayes’ Theorem [Infographic] 2
Brian Wallace is the Founder and President of NowSourcing, an industry leading infographic design agency , based in Louisville, KY and Cincinnati, OH which works with companies that range from startups to Fortune 500s. Brian also runs #LinkedInLocal events nationwide, hosts the Next Action Podcast, and has been named a Google Small Business Advisor for 2016-2018. Follow Brian Wallace on LinkedIn as well as Twitter.

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