We say that a mean-zero random variable X is sub-Gaussian with parameter o2 if the m.g.f. of X satisfies, for all t = R, Mx(t) ≤ e²0²². Let X be a sub-Gaussian random variable with parameter o2. Using Markov's inequality, show that, for all a > 0, P(X ≥ a) ≤ e¯ 20²2 (Hint: the method of proof of the one-sided Chebyshev inequality may provide some in- spiration.)

Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
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Chapter3: Matrices
Section3.7: Applications
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We say that a mean-zero random variable X is sub-Gaussian with parameter
o² if the m.g.f. of X satisfies, for all t ER,
Mx(t) ≤e ²0¹2
Let X be a sub-Gaussian random variable with parameter o². Using Markov's inequality,
show that, for all a > 0,
P(X ≥ a) ≤ e¯20²
(Hint: the method of proof of the one-sided Chebyshev inequality may provide some in-
spiration.)
Transcribed Image Text:We say that a mean-zero random variable X is sub-Gaussian with parameter o² if the m.g.f. of X satisfies, for all t ER, Mx(t) ≤e ²0¹2 Let X be a sub-Gaussian random variable with parameter o². Using Markov's inequality, show that, for all a > 0, P(X ≥ a) ≤ e¯20² (Hint: the method of proof of the one-sided Chebyshev inequality may provide some in- spiration.)
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