Continuous probability distribution
ID: continuous-probability-distribution
A real probability distribution with a continuous cumulative distribution function assigns probability zero to each individual value. Here this is the broad meaning of continuous probability distribution. Many elementary examples are more specifically absolutely continuous probability distributions, described by a probability density function with respect to Lebesgue measure. Some texts use "continuous" for that narrower class. The Cantor distribution shows why the distinction matters: its cumulative distribution function is continuous, yet no probability density function with respect to Lebesgue measure represents its whole law. [ref]
https://ocw.mit.edu/courses/6-436j-fundamentals-of-probability-fall-2018/9797310bed4c7f5b5d40d007783eec8d_MIT6_436JF18_lec04.pdf. MIT Lecture 4: continuous CDFs and the singular Cantor example
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