In mathematics, the Paley–Zygmund inequality bounds the probability that a positive random variable is small, in terms of its first two moments. The inequality was proved by Raymond Paley and Antoni Zygmund. Theorem: If Z ≥ 0 is a random variable with finite variance, and if 0 ≤ θ ≤ 1 {\displaystyle 0\leq \theta \leq 1} , then
P ( Z > θ E [ Z ] ) ≥ ( 1 − θ ) 2 E [ Z ] 2 E [ Z 2 ] . {\displaystyle \operatorname {P} (Z>\theta \operatorname {E} [Z])\geq (1-\theta )^{2}{\frac {\operatorname {E} [Z]^{2}}{\operatorname {E} [Z^{2}]}}.}
Proof: First,
E [ Z ] = E [ Z 1 { Z ≤ θ E [ Z ] } ] + E [ Z 1 { Z > θ E [ Z ] } ] . {\displaystyle \operatorname {E} [Z]=\operatorname {E} [Z\,\mathbf {1} _{\{Z\leq \theta \operatorname {E} [Z]\}}]+\operatorname {E} [Z\,\mathbf {1} _{\{Z>\theta \operatorname {E} [Z]\}}].}
The first addend is at most θ E [ Z ] {\displaystyle \theta \operatorname {E} [Z]} , while the second is at most E [ Z 2 ] 1 / 2 P ( Z > θ E [ Z ] ) 1 / 2 {\displaystyle \operatorname {E} [Z^{2}]^{1/2}\operatorname {P} (Z>\theta \operatorname {E} [Z])^{1/2}} by the Cauchy–Schwarz inequality. The desired inequality then follows. ∎
Related inequalities The Paley–Zygmund inequality can be written as
P ( Z > θ E [ Z ] ) ≥ ( 1 − θ ) 2 E [ Z ] 2 Var Z + E [ Z ] 2 . {\displaystyle \operatorname {P} (Z>\theta \operatorname {E} [Z])\geq {\frac {(1-\theta )^{2}\,\operatorname {E} [Z]^{2}}{\operatorname {Var} Z+\operatorname {E} [Z]^{2}}}.}
This can be improved since, by the Cauchy–Schwarz inequality,
E [ Z − θ E [ Z ] ] ≤ E [ ( Z − θ E [ Z ] ) 1 { Z > θ E [ Z ] } ] ≤ E [ ( Z − θ E [ Z ] ) 2 ] 1 / 2 P ( Z > θ E [ Z ] ) 1 / 2 {\displaystyle \operatorname {E} [Z-\theta \operatorname {E} [Z]]\leq \operatorname {E} [(Z-\theta \operatorname {E} [Z])\mathbf {1} _{\{Z>\theta \operatorname {E} [Z]\}}]\leq \operatorname {E} [(Z-\theta \operatorname {E} [Z])^{2}]^{1/2}\operatorname {P} (Z>\theta \operatorname {E} [Z])^{1/2}}
which, after rearranging, implies that
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