What Is The Bayes Theorem?
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In this 365 Data Science Tutorial we are going to introduce one of the most important formulas in the world of probability- the Bayes’ Rule. People also refer it as the “Bayes’ Law” or “Bayes’ Theorem”.
We begin the video by going over the conditional probability formula and multiplication rule applied on events A and B. You will learn that the Bayes Theorem equation is crucial in helping us find a relationship between the different conditional probabilities of two events .
One of the most prominent examples of using the Bayes’ Rule is in medical research when trying to find a causal relationship between symptoms. Knowing both conditional probabilities between the two help us make more reasonable arguments about which one causes the other. For instance, there is certain correlation between patients with back problems and patients wearing glasses More specifically, 67% of people with back problems wear glasses, while only 41% of people wearing glasses have back pains. These conditional probabilities suggest that it is much more likely for somebody with back problems to wear glasses than the other way around. Even without direct causal link, there exist such arguments to support these claims.
For instance, most people with back pains are elderly or work a desk job, where they remain stationary for long periods of time. Both old age and prolonged work in front of the computer can have a deteriorating effect on the individual’s eyesight, however many healthy individuals wear glasses from a young age. In these situations, there are no other underlying factors that would suggest incoming back pains.
Watch the rest of the video to see how the Bayes Rule is applied in a business setting, more specifically job recruiting, and independent events where we will explore the relationship between weather and code performance.
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