Let ? be a random variable with a PDF
?(?) = |? − 1| for 0 ≤ ? ≤ ?. Answer the following questions
(a) Find ? (b) Find ? (? < 0.5) and ? (|? − 1| > 0.5) (c) Calculate E(?) and V??(?)(?)* Without any computations answer the following questions. Let ? be a random
variable with a PDF
?(?) = 1 − |? − 1| for 0 ≤ ? ≤ ?
for the same ? as in part (a). Which quantity is larger, V??(?) or V??(? )?
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.
1. Let X be a random variable with pdf f(x )-, 0 < x < 2- a) Find the cdf F(x) b) Find the mean ofX.v c) Find the variance of X. d) Find F (1.75) e) Find PG < x < +' f) Find P(X> 1). g) Find the 40th percentile.*
IV. Let X be a random variable with the following pdf: f() = (a + 1)2 for 0<< 1 0 elsewhere Find the maximum likelihood estimator of a, based on a random sample of size n. Check if the Maximum Likelihood Estimator in Part (a) is unbiased
8. Let X and Y be a random variable with joint continuous pdf: f(x,y)- 0< y <1 0, otherwise a. b. c. Find the marginal PDF of X and Y Find the E(X) and Var(X) Find the P(X> Y)
2. Let X be a continuous random variable with pdf f(x) = { cr", [w] <1, f() = 0. Otherwise, where the parameter c is constant (with respect to x). (a) Find the constant c. (b) Compute the cumulative distribution function F(2) of X. (c) Use F(2) (from b) to determine P(X > 1/2). (d) Find E(X) and V(X).
Let X1, ..., X, bei.i.d. random variable with pdf fe defined as follows: fo (2) = 0x0-11(0<x< 1) where 0 is some positive number. Using the MLE Ô, find the shortest confidence interval for 6 with asymptotic level 85% using the plug-in method. To avoid double jeopardy, you may use V for the appropriate estimator of the asymptotic variance V (Ô), and/or I for the Fisher information I (Ô) evaluated at ê, or you may enter your answer without using...
(1) Suppose the pdf of a random variable X is 0, otherwise. (a) Find P(2 < X < 3). (b) Find P(X < 1). (e) Find t such that P(X <t) = (d) After the value of X has been observed, let y be the integer closest to X. Find the PMF of the random variable y U (2) Suppose for constants n E R and c > 0, we have the function cr" ifa > 1 0, otherwise (a)...
Let X be a continuous random variable with the following PDF 6x(1 – x) if 0 < x < 1 fx(x) = 3 0.w. Suppose that we know Y | X = x ~ Geometric(x). Find the posterior density of X given Y = 2, i.e., fxY (2|2).
Suppose that a random variable X has the following pdf: 8px+2(1-P) 0<x<0.5., JxX;P) = *; where 0 Sp Si 0 otherwise where p is simply a constant that has yet to be specified in other words, p is a parameter). For now, we will leave the parameter p an unspecified constant ► Find P(X>0.3) = Note: your answer will be an expression containing p. Suppose that k> 0 is also a constant (not yet specified). Find the expected value of...
2. Let X be a continuous random variable with pdf ( cx?, [xl < 1, f(x) = { 10, otherwise, where the parameter c is constant (with respect to x). (a) Find the constant c. (b) Compute the cumulative distribution function F(x) of X. (c) Use F(x) (from b) to determine P(X > 1/2). (d) Find E(X) and V(X).