Consider an exponentially distributed random variable X with pdf f(x) = 2e−2x for x ≥ 0. Let Y = √X.
a. Find the cdf for Y.
b. Find the pdf for Y.
c. Find E[Y]. If you want to skip a difficult integration by parts, make a substitution and look for a Gamma
pdf.
d. This Y is actually a commonly used continuous distribution. Can you name it and identify its parameters?
e. Suppose that X is exponentially distributed with mean 1/λ. Let Y = X1n. Then we can read
this as Y is the nth root of an exponential random variable. What sort of distribution does Y follow and what are its parameters?
Consider an exponentially distributed random variable X with pdf f(x) = 2e−2x for x ≥ 0....
I. Let Y be an exponentially distributed random variable with parameter λ Compute the cdf and the pdf for the random variable X-e
The random variable X is exponentially distributed, where X represents the waiting time to see a shooting star during a meteor shower. If X has an average value of 11 seconds, what are the parameters of the exponential distribution? Select the correct answer below: a. λ=211, μ=11, σ=112 b. λ=112, μ=11, σ=111 c. λ=11, μ=111, σ=111 d. λ=11, μ=11, σ=111 e. λ=111, μ=11, σ=11
3. Consider a continuous random variable X with pdf given by 0, otherwise This is called the exponential distribution with parameter X. (a) Sketch the pdf and show that this is a true pdf by verifying that it integrates to 1 (b) Find P(X < 1) for λ (c) Find P(X > 1.7) for λ : 1
The moment generating function (MGF) for a random variable X is: Mx (t) = E[e'X]. Onc useful property of moment generating functions is that they make it relatively casy to compute weighted sums of independent random variables: Z=aX+BY M26) - Mx(at)My (Bt). (A) Derive the MGF for a Poisson random variable X with parameter 1. (B) Let X be a Poisson random variable with parameter 1, as above, and let y be a Poisson random variable with parameter y. X...
Let X be a continuous random variable with PDF f(x) = { 3x^3 0<=x<=1 0 otherwise Find CDF of X FInd pdf of Y
(25 points,) Let X and Y be two independent and identically distributed random variables that have exponential distribution with rates 1 respectively. Find the distribution of Note: you can give either cdf or pdf) (25 points,) Let X and Y be two independent and identically distributed random variables that have exponential distribution with rates 1 respectively. Find the distribution of Note: you can give either cdf or pdf)
Let X be an exponential random variable with parameter A > 0, and let Y be a discrete random variable that takes the values 1 and -1 according to the result of a toss of a fair coin Compute the CDF and the PDF of Z = XY Let X be an exponential random variable with parameter A > 0, and let Y be a discrete random variable that takes the values 1 and -1 according to the result of...
Let X be a random variable with pdf S 4x3 0 < x <1 Let Y 0 otherwise f(x) = {41 = = (x + 1)2 (a) Find the CDF of X (b) Find the pdf of Y.
(a) Let X be a continuous random variable with the cdf F(x) and pdf f(.1). Find the cdf and pdf of |X|. (b) Let Z ~ N(0,1), find the cdf and pdf of |Z| (express the cdf using ” (-), the cdf of Z; give the explicit formula for the pdf).
Romeo and Juliet have a date at a given time, denote that random variable X and Y is the amount of time where Romeo and Juliet are late respectively. Assume X and Y are independent and exponentially distributed with different parameters λ and μ, respectively. Find the PDF of X – Y.