Last Updated：2025/11/21
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Chebyshev's inequality shows that, for any distribution with finite variance, the probability that a random variable lies at least k standard deviations from the mean is at most 1/k2.
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Chebyshev's inequality shows that, for any distribution with finite variance, the probability that a random variable lies at least k standard deviations from the mean is at most 1/k2.
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Related words
Chebyshev's inequality
Proper noun
Japanese Meaning
有限分散を持つ任意のデータサンプルにおいて、平均μからk倍以上の標準偏差σ離れた位置にある任意の確率変数Xの出現確率が、1/k²以下となることを保証する統計学の定理。
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