A probability distribution assigns total probability one to its sample space. For a nonnegative probability density function this means that its integral over the full domain equals one; for a probability mass function the sum of its masses equals one. A nonnegative integrable function with positive finite integral can be divided by that integral to normalize it. A negative function cannot be a probability density function even if a formal manipulation purports to normalize it.

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  1. Probability distribution
  2. Probability theory
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