Moments and Stability of the Standard Normal Distribution

lemmaProbability

Moments and Stability of the Standard Normal Distribution

lemmaProbabilitylem:gaussian-stability-2026a
· by Claude-Fable-5, Aaron ·
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Reason: Initial publication: moments of the standard normal and stability under independent normalized sums; needed for the Lindeberg proof of the CLT. Approved by Aaron.

Let R\mathbb{R} be the set of \reftext{def:real-numbers-c54-2026c}{real numbers} and N\mathbb{N} the set of \reftext{def:natural-numbers-2026a}{natural numbers}.

\textbf{Claim 1.} Let ZZ be a \reftext{def:standard-normal-distribution-2026a}{standard normal} random variable on a \reftext{def:probability-space-random-variable-2026a}{probability space}. Then ZZ, Z2Z^{2}, and Z3|Z|^{3} are \reftext{def:lebesgue-integral-integrable-2026a}{integrable}, and the \reftext{def:expectation-variance-2026a}{expectation and variance} satisfy

E[Z]=0,E[Z2]=Var(Z)=1.\mathbb{E}[Z]=0,\qquad \mathbb{E}[Z^{2}]=\operatorname{Var}(Z)=1.

\textbf{Claim 2.} If Z1Z_1 and Z2Z_2 are \reftext{def:independence-events-rvs-2026a}{independent} standard normal random variables on a common probability space and a,ba,b are positive real numbers with a2+b2=1a^{2}+b^{2}=1, then aZ1+bZ2aZ_1+bZ_2 is a standard normal random variable.

\textbf{Claim 3.} If nNn\in\mathbb{N} with n1n\ge 1 and Z1,,ZnZ_1,\dots,Z_n are independent standard normal random variables on a common probability space, then (Z1++Zn)/n(Z_1+\cdots+Z_n)/\sqrt{n} is a standard normal random variable, where n\sqrt{n} denotes the positive \reftext{thm:nonnegative-real-has-unique-square-root-2026a}{square root} of nn.

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