#concentration_inequality
Concentration inequality
Mathematical inequality explaining concentration of random variables
In probability theory, concentration inequalities provide mathematical bounds on the probability of a random variable deviating from some value. The deviation or other function of the random variable can be thought of as a secondary random variable. The simplest example of the concentration of such a secondary random variable is the CDF of the first random variable which concentrates the probability to unity. If an analytic form of the CDF is available this provides a concentration equality that provides the exact probability of concentration. It is precisely when the CDF is difficult to calculate or even the exact form of the first random variable is unknown that the applicable concentration inequalities provide useful insight.
Mon 2nd
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