How to understand Bayes rule in simple terms?
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“I don’t have the authority to explain complex mathematics.” But let me make a simple explanation, as simple as possible. Here’s what Bayes is all about — it’s a concept that deals with probability and makes sense out of randomness. So, what does it do? Here’s an easy-to-follow explanation: Let’s say you’re ordering a pizza, and you’re going to pick the cheese, veggies and pepperoni. You may have to make choices, but you know you
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“Bayes is a fundamental theorem in statistics that states that given that a certain statement is true, its probability of being true must also be true. In other words, if A is true, the probability of B being true must also be true.” I wrote as I have to provide a simple explanation. Section: In the world, we hear lots of stories about things that are going to happen in the future. We say, “When you see a blue sky, you should not jump off the roof of the house,” or
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Bayes is an essential part of probability theory. Bayes is also known as conditional probability. It is based on the concept of likelihood. Let me first explain what likelihood is and then I’ll explain how it relates to Bayes . my explanation Likelihood is a measure of the likelihood of something happening in the future given a certain present state. In Bayes , a probability distribution represents how likely a certain outcome is, given certain assumptions about the events leading to that outcome. So, let me explain what likelihood means. Likelihood
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“Bayes is a fundamental concept that aids us in understanding probability distributions and decision-making. Here I’ll explain Bayes using an example.” Bayes is a mathematical formula that involves the probability of something happening, given that something else happened or not happened. It is based on the law of chance, a principle which states that events follow a certain pattern or chance. Let us consider a situation where we have two events: – A is the event and B is the other event. – The probability of A occurring given B is
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I believe the term Bayes comes from an old French word “Bayesia”, which means the ratio of possible to the probabilities, thus the meaning of the is “Bayes factor”. It has come to be in mathematics, statistics and artificial intelligence. “Bayes” stands for “beliefs and priors”, and “factors” refers to parameters of the decision. The states that, when a subjective opinion and evidence are in agreement, the belief becomes certain. Let’s try to understand this in simple terms
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The Bayes is a fundamental tool in decision-making, in which the probability of a hypothesis given evidence is multiplied with the prior probability of that hypothesis. In the formula, p is the prior probability of the hypothesis, H0, and H1 is the alternative hypothesis. Bayes is often used in clinical trials and other scientific investigations, as it provides a systematic and statistical way to evaluate hypotheses. In this formula, the prior probability of H0 is 1, meaning that there is a 100% probability that H0