Question

Let X1,...,X99 be independent random variables, each one distributed uniformly on [0, 1]. Let Y denote...

Let X1,...,X99 be independent random variables, each one distributed uniformly on [0, 1]. Let Y denote the 50th largest among the 99 numbers. Find the probability density function of Y.

Homework Answers

Answer #1

Answer:-

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Let X1, X2, X3 be independent random variables, uniformly distributed on [0,1]. Let Y be the...
Let X1, X2, X3 be independent random variables, uniformly distributed on [0,1]. Let Y be the median of X1, X2, X3 (that is the middle of the three values). Find the conditional CDF of X1, given the event Y = 1/2. Under this conditional distribution, is X1 continuous? Discrete?
Let X and Y be independent; each is uniformly distributed on [0, 1]. Let Z =...
Let X and Y be independent; each is uniformly distributed on [0, 1]. Let Z = X + Y. Find: E[Z|X]. Your answer should be a function of x.
Let Xi, i = 1, 2..., 48, be independent random variables that are uniformly distributed on...
Let Xi, i = 1, 2..., 48, be independent random variables that are uniformly distributed on the interval [-0.5, 0.5]. (a) Find the probability Pr(|X1|) < 0.05 (b) Find the approximate probability P (|Xbar| ≤ 0.05). (c) Determine an approximation of a such that P(Xbar ≤ a) = 0.15
Let Y be the liner combination of the independent random variables X1 and X2 where Y...
Let Y be the liner combination of the independent random variables X1 and X2 where Y = X1 -2X2 suppose X1 is normally distributed with mean 1 and standard devation 2 also suppose the X2 is normally distributed with mean 0 also standard devation 1 find P(Y>=1) ?
Suppose that X1 and X2 are independent continuous random variables with the same probability density function...
Suppose that X1 and X2 are independent continuous random variables with the same probability density function as: f(x) = ( x 2 0 < x < 2, 0 otherwise. Let a new random variable be Y = min(X1, X2,). a) Use distribution function method to find the probability density function of Y, fY (y). b) Compute P(Y > 1).
Let {Xj} ∞ j=1 be a collection of i.i.d. random variables uniformly distributed on [0, 1]....
Let {Xj} ∞ j=1 be a collection of i.i.d. random variables uniformly distributed on [0, 1]. Let N be a Poisson random variable with mean n, and consider the random points {X1 , . . . , XN }. b. Let 0 < a < b < 1. Let C(a,b) be the number of the points {X1 , . . . , XN } that lies in (a, b). Find the conditional mass function of C(a,b) given that N =...
Suppose that X1 and X2 are independent continuous random variables with the same probability density function...
Suppose that X1 and X2 are independent continuous random variables with the same probability density function as: f(x) = ( x 2 0 < x < 2, 0 otherwise. Let a new random variable be Y = min(X1, X2,). a) Use distribution function method to find the probability density function of Y, fY (y). b) Compute P(Y > 1). c) Compute E(Y )
Let X1, X2 be two normal random variables each with population mean µ and population variance...
Let X1, X2 be two normal random variables each with population mean µ and population variance σ2. Let σ12 denote the covariance between X1 and X2 and let ¯ X denote the sample mean of X1 and X2. (a) List the condition that needs to be satisfied in order for ¯ X to be an unbiased estimate of µ. (b) [3] As carefully as you can, without skipping steps, show that both X1 and ¯ X are unbiased estimators of...
Let X and Y be independent random variables, uniformly distribued on the interval [0, 2]. Find...
Let X and Y be independent random variables, uniformly distribued on the interval [0, 2]. Find E[e^(X+Y) ].
Let X1 and X2 be two independent geometric random variables with the probability of success 0...
Let X1 and X2 be two independent geometric random variables with the probability of success 0 < p < 1. Find the joint probability mass function of (Y1, Y2) with its support, where Y1 = X1 + X2 and Y2 = X2.