I. Let Y be an exponentially distributed random variable with parameter λ Compute the cdf and...
3. Suppose that X and Y are independent exponentially distributed random variables with parameter λ, and further suppose that U is a uniformly distributed random variable between 0 and 1 that is independent from X and Y. Calculate Pr(X<U< Y) and estimate numerically (based on a visual plot, for example) the value of λ that maximizes this probability.
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...
If X is uniformly distributed over (0,2) and Y is exponentially distributed with parameter λ = 2. Also X and Y are independent, find the PDF of Z = X+Y.
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 an exponentially distributed random variable with parameter λ. Prove that P(X > s + tK > t) P(X > s) for any S,12 0
Let X be exponentially distributed with parameter 3. a) Compute P(X > 6 | X > 2). b) Compute E(7e-12x+8+ 5). c) Let Y be independent from X. Suppose the PDF for Y is f(x) = 2x for 0 ≤ x ≤ 1 (and 0 else). Find the PDF of X + Y.
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 ].
5. A light bulb has a lifetime that is exponentially distributed with rate parameter λ-5. Let L be a random variable denoting the sum of the lifetimes of 50 such bulbs. Assume that the bulbs are independent. (a) Compute E[L] and Var(L). b) Use the Central Limit Theorem to approximate P(8 < L < 12 ( ). (c) Use the Central Limit Theorem to find an interval (a,b), centered at ELLI, such that Pa KL b) 0.95. That is, your...
Let X be a continuous random variable, and let Y = g(X), where g(x) = { 0; x < 0 or x > 3 { x; 0 <= x < 1 { 1; 1 <= x < 2 { 3-x; 2 <= x <= 3 (a) Express the cdf of Y in terms of the cdf of X. (b) Determine and sketch the cdf of Y when X is exponentially distributed with parameter α = 1. Is the cdf of...
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