Table of Contents

Summary:

  • $ P(x; \theta) $: A parameterized probability distribution with parameters $ \theta $.
    • $ x $ means a random variable, $ \theta $ represents the parameters of distribution.
    • Example: In a normal distribution $ P(x; \mu, \sigma) $, parameters $ \mu $ and $ \sigma $ respectively represent mean and standard deviation.
  • $ P(x \mid \theta) $: The conditional probability of $ x $ given events $ \theta $ has occurred or is known.
    • Example: In Bayesian statistics, a likelihood function $ P(x; \theta) $ represents the probability of the observed data $ x $ given the parameter $ \theta $.

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