posterior probability - Deepstash

posterior probability

Typically written as P(H|E) in Bayes’s theorem, it is the result of conditionalizing a hypothesis H on an incoming piece of evidence E, read as “the probability of the hypothesis given the evidence.”

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Key Concepts in Statistics

We often feel anecdotes from people we know more persuasive than scientific evidence. This is because we don’t understand statistics well.

3 key concepts we must always remember:

  1. Law of Large Number (more data in a sample, more accurate conclusion)

Common Probability Distributions

The common probability distributions are:

  1. Uniform Distribution: It is a simple off or on distribution, where anything outside the given range is 0.
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Thomas Bayes'd thought experiment

Thomas Bayes'd thought experiment

He wondered how he could predict the probability of a future event if he only knew how many times it had occurred, or not, in the past. Bayes figured out that even when it comes to uncertain outcomes, we can update our knowledge by incorporating new, relevant information as it becomes available.

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