We have the distribution of X here as:
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:
Now we will use the taylor expansion of Ln(1 + x) here which is given as:
Putting x = (1-p) here, we get:
This is the required expected value of g(x) here.
pls help Exercise 5.6. Suppose that X is a random variable which has geometric distribution with...
Exercise 5.6. Suppose that X is a random variable which has geometric distribution with parameter p, for some pe (0,1). Compute E[9(X)], where So if t = 0, g(t) = if t +0. 11/t
Exercise 5.6. Suppose that X is a random variable which has geometric distribution with parameter p, for some pe (0,1). Compute E[g(X)], where so if t = 0, g(t) = 11/t if t +0.
5. Suppose X is a discrete random variable that has a geometric distribution with p= 1. a. Compute P(X > 6). [5] b. Use Markov's Inequality to estimate P(X> 6). [5] c. Use Chebyshev's Inequality to estimate P(X>6). [5] t> 0 6. Let be the probability density function of the continuous 0 t< 0 random variable X. a. Verify that g(t) is indeed a probability density function. [8] b. Find the median of X, i.e. the number m such that...
4. (9 pts) Suppose the random variable Y has a geometric
distribution with parameter p. Let ?? = √?? 3 3 . Find the
probability distribution of V
3 4. (9 pts) Suppose the random variable Y has a geometric distribution with parameter p. Let V 3 Find the probability distribution of.
Question 1: 1a) Let the random variable X have a geometric distribution with parameter p , i.e., P(X = x) = pq??, x=1,2,... i) Show that P(X > m)=q" , where m is a positive integer. (5 points) ii) Show that P(X > m+n X > m) = P(X>n), where m and n are positive integers. (5 points) 1b) Suppose the random variable X takes non-negative integer values, i.e., X is a count random variable. Prove that (6 points) E(X)=...
Exercise 2.23 If X is a discrete random variable having the Poisson distribution with parameter that the probability that X is even is e cosh A. Exercise 2.24 If X is a discrete random variable having the geometric distribution with parameter p. show that the probability that X is greater than k is (1 -p)k à, show
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Problem 4 A discrete random variable X follows the geometric distribution with parameter p, written X ~Geom(p), if its distribution function is fx(x) = p(1-p)"-1, xe(1, 2, 3, . . .} The Geometric distribution is used to model the number of flips needed before a coin with probability p of showing Heads actually shows Heads. a) Show that Ix(z) is indeed a probability inass function, i.e., the sum over all possible values of z is one...
3. Consider a discrete random variable X which follows the geometric distribution f(x,p) = pr-1(1-p), x = 1.2. . . . , 0 < p < 1. Recall that E(x) (1-p) (a) Find the Fisher information I(p). (b) Show that the Cramer-Rao inequality is strict e) Let XX ~X. Find the maximum likelihood estimator of p. Note that the expression you find may look complicated and hard to evaluate. (d) Now modify your view by setting μ T1p such that...
Problem 8 (10 points). Let X be the random variable with the geometric distribution with parameter 0 <p <1. (1) For any integer n > 0, find P(X >n). (2) Show that for any integers m > 0 and n > 0, P(X n + m X > m) = P(X>n) (This is called memoryless property since this conditional probability does not depend on m. Dobs inta T obabilita ndomlu abonn liaht bulb indofootin W
2 5. Suppose X is a discrete random variable that has a geometric distribution with p= a. Compute P(X > 6). [5] b. Use Markov's Inequality to estimate P(X > 6). [5] c. Use Chebyshev's Inequality to estimate P(X > 6). [5]