9. Let X be a Poisson random variable with parameter k = 3. (a) P[X 25]...
Show all details: Exercise 10.4. Let X be a Poisson random variable with parameter λ. That is, P(X = k) e-λλk/kl, k 0.1 Compute the characteristic function of (X-λ)/VA and find its limit as Exercise 10.4. Let X be a Poisson random variable with parameter λ. That is, P(X = k) e-λλk/kl, k 0.1 Compute the characteristic function of (X-λ)/VA and find its limit as
Let X be a Poisson random variable with parameter λ = 6, and let Y = min(X, 12). (a) What is the p.m.f. of X? (b) What is the mean of X? (c) What is the variance of X? (d) What is the p.m.f. of Y? (e) Compute E[Y ].
3. Let X be a random variable from a geometric distribution with parameter p (P(X- k p(1-P)"-, } k-1 k-1, 2, ...). Find Emin{X, 100
5. Let X be a Poisson random variable with parameter λ = 6, and let Y = min(X, 12). (a) What is the p.m.f. of X? (b) What is the mean of X? (c) What is the variance of X? (d) What is the p.m.f. of Y? (e) Compute EY
If X is a Poisson random variable with parameter ?, show that the Tchebyshev’s inequality will indicate P(0 < X < 21) >1–
5. Let X be a Poisson random variable with parameter λ 6, and let Y-min(X,12 (a) What is the p.m.f. of X? (b) What is the mean of X? (c) What is the variance of X? (d) What is the p.m.f. of Y? (e) Compute E[Y].
3. Let X be a geometric random variable with parameter p. Prove that P(X >k+r|X > k) = P(X > r). This is called the memoryless property of the geometric random variable.
1. The random variable X is Gaussian with mean 3 and variance 4; that is X ~ N(3,4). $x() = veze sve [5] (a) Find P(-1 < X < 5), the probability that X is between -1 and 5 (inclusive). Write your answer in terms of the 0 () function. [5] (b) Find P(X2 – 3 < 6). Write your answer in terms of the 0 () function. [5] (c) We know from class that the random variable Y =...
> 0, that is 7. Let X has a Poisson distribution with parameter P(X = x) = e- Tendte 7. x = 0, 1, 2, .... Find the variance of X.
3, Let X be a Poisson random variable with parameter λ. Calculate the conditional expectation of X given that X is odd.