Bayes\u2019 Theorem is a way to calculate\u00a0<\/span>conditional probability<\/a>. The formula is very simple to calculate, but it can be challenging to fit the right pieces into the puzzle. The first challenge comes from defining your event (A) and test (B); The second challenge is rephrasing your question so that you can work backwards: turning P(A|B) into P(B|A). The following image shows a basic example involving website traffic. For more simple examples, see: Bayes Theorem Problems<\/a>.<\/span> Click on picture to zoom in\u00a0<\/em><\/p>\n For related content about Bayes theorem and Bayesian statistics, follow this link<\/a> or this one<\/a>. For other machine learning concepts explained in one picture, follow this link<\/a>. For statistical concepts explained in simple English, follow this link<\/a>. To subscribe to our newsletter, click here<\/a>.\u00a0<\/p>\n<\/div>\n Go to Source<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<\/a><\/p>\n