Here is one way to think about a mixed random variable. Suppose that we have a discrete random variable Xa with (generalized) PDF and CDF fa(r) and Fa(x), and a continuous random variable X. with PDF and CDF f.(r) and F.(x). Now we create a new random variable X in the following way. We have a coin with P(H) = p. We toss the coin once. If it lands heads, then the value of X is determined according to the probability distribution of X4. If the coin lands tails, the value of X is determined according to the probability distribution of Xe. a. Find the CDF of X, Fx(x). b. Find the PDF of X, fx(x). c. Find EX.

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A: Given : V(X)=11 and Y=2X−4 V(Y) = V(2X−4) = 22V(X) = 4*11 = 44

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Q: uted random variables, that is, they are defined on the same sample space. = 5 )=26 Dw.

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A: Given that ; E(x) = 0            ;     v(x) = 39 E(y) = -4        ;      v(y) = 19 E(z) = 6        ;…

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A: GivenE(X)=5E(Y)=-7E(Z)=3Var(X)=20Var(Y)=6Var(Z)=23

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