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Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory.

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Comparison of Rademacher and Gaussian expected values under linear transformations

At the end I'm not sure if you want $G$ to be a standard Gaussian or a Rademacher? If $G$ were to be a Rademacher, then consider the function $f$ such that $f(-1)=f(1)=0$ and $f(x)=1$ if $x\not\in\{-1 …
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