For each of the 4 components, the lifetime distribution here is given as:
Therefore the probability that any of the components lasts at least 310 hours is computed here as:
Converting it to a standard normal variable, we have here:
This is obtained from the standard normal tables as:
Now the probability that out of 4 such components, at least 2 of the four chips lasts at least 310 hours is computed using Binomial probability function as:
This is the required probability expression here.
11. Let X1, X2, X3 and X4 be independent lifetimes of memory chips. Suppose that Xi...
14. Let X1, X2, X3 be independent random variables that represent lifetimes (in hours) of three key components of a device. Suppose their respective distributions are exponential with means 1000, 1500, and 2000. Let Y be the minimum of Xi, X2, X3 and compute P(Y 1000).
4. Let T = min(Xi, X2,Xy), where each Xi~Weibull(8,a) and X1, X2, X3 are independent (component lifetimes). Show that T also has a Weibull distribution exactly with some shape and scale parameters. (This is so-called "weakest-link model" Hint: find the reliability function of T.)
4. Let T = min(Xi, X2,Xy), where each Xi~Weibull(8,a) and X1, X2, X3 are independent (component lifetimes). Show that T also has a Weibull distribution exactly with some shape and scale parameters. (This is so-called "weakest-link model" Hint: find the reliability function of T.)
Let X1, X2, X3 … be independent random variable with P(Xi = 1) = p = 1-P(Xi=0), i ≥ 1. Define: N1 = min {n: X1+…+ Xn =5}, N2 = 3 if X1 = 0, 5 if X1 = 1. N3 = 3 if X4 = 0, 2 if X4 = 1. Which of the Ni are stopping times for the sequence X1, …?
If X1, X2, and X3 are three independent Uniform random variables (Xi-Unif(0,1)) a) Use the convolution integral to find density function of Z-x1+X2+X3. b) What is E[Z]? independent Uniform random variables (Xi-Unifo,1): If X1, X2, and X3 are three independent Uniform random variables (Xi-Unif(0,1)) a) Use the convolution integral to find density function of Z-x1+X2+X3. b) What is E[Z]? independent Uniform random variables (Xi-Unifo,1):
Suppose that X1, X2, X3 and X4 are independent Poisson where E[X1] = lab E[X2] = 11 – a)b E[X3] = da(1 – b) E[X2] = X(1 — a)(1 – b) for some a and b between 0 and 1. Let S = X1 + X2+X3+X4, R= X1 + X2 and C = X1 + X3. (a) Find P(R = 10) (b) Find P(X1 = 6 S = 16 and R= 12). (c) Suppose we want to condition on the...
3. (25 pts.) Let X1, X2, X3 be independent random variables such that Xi~ Poisson (A), i 1,2,3. Let N = X1 + X2+X3. (a) What is the distribution of N? (b) Find the conditional distribution of (X1, X2, X3) | N. (c) Now let N, X1, X2, X3, be random variables such that N~ Poisson(A), (X1, X2, X3) | N Trinomial(N; pi,p2.ps) where pi+p2+p3 = 1. Find the unconditional distribution of (X1, X2, X3). 3. (25 pts.) Let X1,...
Let x1, x2, x3, x4 be independent standard normal random variables. Show that , , are independent and each follows a distribution (x1 - r2)
3. Let {X1, X2, X3, X4} be independent, identically distributed random variables with p.d.f. f(0) = 2. o if 0<x< 1 else Find EY] where Y = min{X1, X2, X3, X4}.
Suppose we have 5 independent and identically distributed random variables X1, X2, X3, X4,X5 each with the moment generating function 212 Let the random variable Y be defined as Y = Σ Find the joint probability that all Xi, (i-1,.5), are larger than 9.