Construct examples of distributions for X such that, (a) The Markov inequality is tight, i.e., there...

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Construct examples of distributions for X such that, (a) The Markov inequality is tight, i.e., there exists a distribution Fx (x) and a point a E R such that P(X ≥ a) = (E(X)/a). (b) The Chebyshev inequality is tight, i.e., there exists a distribution Fx (x) and a point a > 0, a ER such that P(|X - E(X)| ≥ a) = (o/a²). Construct examples of distributions for X such that, (a) The Markov inequality is tight, i.e., there exists a distribution Fx (x) and a point a E R such that P(X ≥ a) = (E(X)/a). (b) The Chebyshev inequality is tight, i.e., there exists a distribution Fx (x) and a point a > 0, a ER such that P(|X - E(X)| ≥ a) = (o/a²).

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