Markov Inequality
Markov Inequality is a fundamental theorem in probability theory that provides an upper bound on the probability that a non-negative random variable exceeds a positive multiple of its expected value, expressed as \( P(X \geq a) \leq \frac{\mathbb{E}[X]}{a} \) for \( a > 0 \).
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5.5K
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142
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106
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2017–2026
9
Variants
Markov's Inequality
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Institute of Mathematics
Warsaw, Poland
5 h-index
7 publications
289 citations
Jagiellonian University
Krakow, Poland
5 h-index
7 publications
179 citations
Montanuniversität Leoben
Leoben, Austria
5 h-index
6 publications
117 citations

University of Toronto
Toronto, Canada
4 h-index
7 publications
244 citations
Texas A&M University
College Station, United States
4 h-index
4 publications
187 citations
The Ohio State University
Columbus, United States
4 h-index
4 publications
115 citations
Simon Fraser University
Burnaby, Canada
3 h-index
5 publications
152 citations

University of Auckland
Auckland, New Zealand
2 h-index
2 publications
30 citations
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17 publications · 516 citations
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6 publications · 91 citations
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TRAN · 4 publications · 89 citations
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3 publications · 75 citations
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3 publications · 38 citations
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