The variance can be written as Var[X]=E[X^2]-(E[X])^2. Use this form to prove that the Var[X] is always non-negative, i.e., show that E[X^2]>=(E[X])^2.(adsbygoogle = window.adsbygoogle || []).push({});

Use Jensen's Inequality.

Any sugestions? I just tried to prove that a function g(t) is continuous and twice differentiable, such that g''(t) > 0 which must imply it is convex.

Then, I am stuck with the proof.

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# Jensen's Inequality

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