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Exercise 5.6. Suppose that X is a random variable which has geometric distribution with parameter p, for some pe (0,1). Compu

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Answer #1

We have the distribution of X here as:

X \sim Geometric(p)

As the value of X can never be 0, therefore the function g(X) here is given as:

G(x) = 1/x

P(X = 1) = p
P(X = 2) = (1-p)p
P(X = 3) = (1-p)2p and so on.....

Therefore,
P(G(x) = 1) = p
P(G(x) = 1/2) = (1-p)p
P(G(x) = 1/3) = (1-p)2p and so on...

Therefore the expected value of g(X) here is computed as:

E(G(x)) = \sum t P(G(x) = t)

E(G(x)) = p + \frac{(1-p)p}{2} + \frac{(1-p)^2p}{3} + ... \infty

E(G(x)) = p(1+ \frac{(1-p)}{2} + \frac{(1-p)^2}{3} + ... \infty )

Now we will use the taylor expansion of Ln(1 + x) here which is given as:

Ln(1 + x) = x - \frac{x^2}{2} + \frac{x^3}{3} - \frac{x^4}{4} + ....\infty

Ln(1 - x) = - x - \frac{x^2}{2} - \frac{x^3}{3} - \frac{x^4}{4} + ....\infty

Putting x = (1-p) here, we get:

Ln(p) = - ((1 -p) + \frac{(1-p)^2}{2} + \frac{(1-p)^3}{3} + \frac{(1-p)^4}{4} + ....\infty )

Ln(p) = -(1-p) (1 + \frac{(1-p)}{2} + \frac{(1-p)^2}{3} + \frac{(1-p)^3}{4} + ....\infty )

Ln(p) = -(1-p) E(g(X))

E(g(x)) = \frac{Ln(p)}{p-1}

This is the required expected value of g(x) here.

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