Markov inequality

Markov inequality

[′mar‚kȯf ‚in·i′kwäl·əd·ē]
(statistics)
If x is a random variable with probability P and expectation E, then, for any positive number a and positive number n P (| x | ≥ a) ≤ E (| x |n/ a n).
References in periodicals archive ?
Since [tau] < 3, the Markov inequality and a basic property (see e.
11) and the Markov inequality that for any t > 0 and some constant C > 0,
Exploiting the Markov inequality, dominated convergence theorem and (3.
Markov inequality entails that the conditional probability that [tau.
Then by the Markov inequality [1] for any x [member of] [I.
Both Remez and Markov inequalities are well developed in the multivariate setting but the approach using Markov inequality seems to be more suitable for several variables.