Let Y1, Y2, . . . , Yn be independent random variables with Exponential distribution with mean β. Let Y(n) = max(Y1,Y2,...,Yn) and Y(1) = min(Y1,Y2,...,Yn). Find the probability P(Y(1) > y1,Y(n) < yn).
Let Y1, Y2, . . . , Yn be independent random variables with Exponential distribution with...
Let Y1, Y2, ..., Yn be independent random variables each having uniform distribution on the interval (0, θ) (c) Find var(Y(j) − Y(i)). Let Y İ, Y2, , Yn be independent random variables each having uniform distribu- tion on the interval (0,0) Let Y İ, Y2, , Yn be independent random variables each having uniform distribu- tion on the interval (0,0)
Let Y1, Y2, . .. , Yn be independent and identically distributed random variables such that for 0 < p < 1, P(Yi = 1) = p and P(H = 0) = q = 1-p. (Such random variables are called Bernoulli random variables.) a Find the moment-generating function for the Bernoulli random variable Y b Find the moment-generating function for W = Yit Ye+ … + . c What is the distribution of W? 1.
Let Y1, Y2, ..., Yn be independent random variables each having uniform distribution on the interval (0, θ). Find variance(Y(j) − Y(i)) Let Yİ,Y2, , Yn be independent random variables each having uniform distribu - tion on the interval (0,0) Fin ar(Y)-Yo
Suppose Y1, Y2, …, Yn are independent and identically distributed random variables from a uniform distribution on [0,k]. a. Determine the density of Y(n) = max(Y1, Y2, …, Yn). b. Compute the bias of the estimator k = Y(n) for estimating k.
Let Y1, Y2, ..., Yn be independent random variables each having uniform distribution on the interval (0, θ). (a) Find the distribution of Y(n) and find its expected value. (b) Find the joint density function of Y(i) and Y(j) where 1 ≤ i < j ≤ n. Hence find Cov(Y(i) , Y(j)). (c) Find var(Y(j) − Y(i)). Let Yİ, Ya, , Yn be independent random variables each having uniform distribu- tion on the interval (0, 6) (a) Find the distribution...
Let Y1<Y2<...<Yn be the order statistics of a random sample of size n from the distribution having p.d.f f(x) = e-y , 0<y<, zero elsewhere. Answer the following questions. (a) decide whether Z1 = Y2 and Z2=Y4-Y2 are stochastically independent or not. (hint. first find the joint p.d.f. of Y2 and Y4) (b) show that Z1 = nY1, Z2= (n-1)(Y2-Y1), Z3=(n-2)(Y3-Y2), ...., Zn=Yn-Yn-1 are stocahstically independent and that each Zi has the exponential distribution.(hint use change of variable technique)
Let Y1, Y2, , Yn be independent, normal random variables, each with mean μ and variance σ^2. (a) Find the density function of f Y(u) = (b) If σ^2 = 25 and n = 9, what is the probability that the sample mean, Y, takes on a value that is within one unit of the population mean, μ? That is, find P(|Y − μ| ≤ 1). (Round your answer to four decimal places.) P(|Y − μ| ≤ 1) = (c)...
Let Y1, Y2, ..., Yn denote a random sample from an exponential distribution with mean θ. Find the rejection region for the likelihood ratio test of H0 : θ = 2 versus Ha : θ ≠ 2 with α = 0.09 and n = 14. Rejection region =
QUESTION 3 Let Y1, Y2, ..., Yn denote a random sample of size n from a population whose density is given by (Parcto distribution). Consider the estimator β-Yu)-min(n, Y, where β is unknown (a) Derive the bias of the estimator β. (b) Derive the mean square error of B. , Yn).
Suppose Y1, Y2, ... Yn are mutually independent random variables with Y1 ~ N(μ1, (σ1)^2) Y2 ~ N(μ2, (σ2)^2) ... Yn ~ N(μn, (σn)^2) Find the distribution of U=summation(from i=1 to n) ((Yi - μi)/σi)^2 I am not sure where should I start this question, could you please show me the detail that how you do these two parts? thanks :)