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Bayes’ Theorem
Bayes’ Theorem is my all-time favorite statistical theory. It helps us understand what seems like straightforward problems in probability with counter-intuitive solutions! Like what is the…
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Ever wondered about calculating the probability of an event based on some other event, it would have been fun right! If till now you have not figured out trying the above scenario, I will help you…
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The fundamental idea of Bayesian inference is to become “less wrong” with more data. The process is straightforward: we have an initial belief, known as a prior, which we update as we gain additional…...
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It is always believed that the past experience always effects the current decision making. This concept cannot be better explained than the Bayes Theorem in Statistics. Here in this blog I want to…
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Bayes’ Theorem is a simple mathematical formula used for calculating conditional probabilities. It figures prominently in subjectivist or Bayesian approaches to epistemology, statistics, and…
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When you hear of probability, you remember that one chapter you had left as a choice in your 12th grade, right? Well, you might have had ignored it in your 12th grade, but you never did ignore it in…
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It’s one of the most famous equations in the world of statistics and probability. Even if you don’t work in a quantitative field, you’ve probably had to memorize it at some point for an exam. But…
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If I had to guess, most of the statistical theory you’ve learned has been from a Frequentist’s prism. T-tests, z-tests, p-values, and ANOVA, just to name a few, are all from the viewpoint of…
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Bayes’ Theorem provides a way to calculate updated probability of an event when new information becomes available. Simply put, it is a way of calculating conditional probability. In this post, we…
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Recently I am reading books related to history of mathematics, which reminds me of the fact that all complicated-looking equations started from a small, real world problem. The benefits of studying…
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In real life, we can know the number of occurrences of an event relative to other events. For example, let's throw a fair dice. We understand that each face has an equal chance to appear, so we say…
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A simple and intuitive explanation of conditional probability and Bayes’ theorem. Continue reading on Towards AI
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