there is nothing wrong with the question. Question 1 Let X be a random variable from...
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distribution. 0 and check that the mode of the generated samples is close to the (check the histogram). theoretical mode mass function 3.5 A discrete random variable X has probability 3 4 AtB.8 HUS 2 X p(x) 0.1 0.2 0.2 0.2 0.3 a random sample of size Use the inverse transform method to generate 1000 from the distribution of X. Construct a relative frequency table and compare the empirical with the theoretical probabilities. Repeat using the R sample function....
Question Let X be a continuous random variable with the following probability density function (pdf) 0.5e fx (x) = { 0.5e-1 x < 0. <>0.. (a) Show that fx (x) is a valid pdf. (b) Find the cumulative distribution function Fx (.x). (e) Find F='(X). (d) Write an algorithm to generate a sample of size 1000 from the distribution of X using the inverse-transform method. Be as precise as possible.
Develop a generator for a random variable whose pdf is F(x) ={ 1/3, 0<=x<=2 1/24, 2<x<=10 0, otherwise a) Write a computer routine to generate 1000 values. b) Plot a histogram of 1000 generated values. c) Perform goodness-of-fit test to determine whether these generated values fits the theoretical density function given above. Note: Invlude your computer routine for generating random variates in your answer sheet. I need numerical solution
9. Let X be a Poisson random variable with parameter k = 3. (a) P[X 25] (b) Find P[5 S X <10) (c) Find the variance ? 10. Use the related Table to find the following: (here Z represents the standard normal variable) (a) P[Z > 2.57] (b) The point z such that PL-2 SZ sz]=0.8
need the solution for this question.tq
Let X,,. X, be a random sample from a Poisson (a) (a). 2. distribution. Find the sufficient statistic for A. (25 marks) Let X,X,X, be a random sample from a gamma (k, B) (b). P.1 distribution with k is fixed. DefineX X, n피 based upon unbiased ness, consistency Evaluate (0). and efficiency is a minimum variance unbiased estimator for B Show that (ii). (75 marks) (2)3
Let X,,. X, be a random sample from...
QUESTION 3 17) Let Xi. X. X be a random sample from a distribution with probability density function f(x, ?) | ße_ß, for x >0 elsewhere (a) What is the likelihood (LU) = L (x1.X2. xalß)) of the sample? Simplify it. (b) Use the factorization criterion/theorem to show that ? x, is a sufficient statistic for . 4
Question.1 (11 Marks] Let X be a random variable with the following pdf: f(x; 8) 1>0, >0. 1 (1) (a) Show that I f(x;0)d.r = 1 (b) is the pdf f(c;) member of the Exponential family distributions? Justify in details your answer (c) Find a sufficient statistic for the unknown parameter 8. (d) Find a maximum likelihood estimator for 6.
Find the variance of random variable X. 7.. Let X be a continuous random variable whose probability density function is: -(2x3 + ar', if x E (0:1) if x (0;1) Find 1) the coefficient a; 2) P(O.5eX<0.7); 3) P(X>3). Part 3. Statistics A sample of measurements is given X 8 -2 0 2 8
If X is a Poisson random variable with parameter ?, show that the Tchebyshev’s inequality will indicate P(0 < X < 21) >1–
Poisson Distribution Question
Problem 2: Let the random variable X be the number of goals scored in a soccer game, and assume it follows Poisson distribution with parameter λ 2, t 1, i.e. X-Poisson(λ-2, t Recall that the PMF of the Poisson distribution is P(X -x) - 1) e-dt(at)*x-0,1,2,.. x! a) Determine the probability that no goals are scored in the game b) Determine the probability that at least 3 goals are scored in the game. c) Consider the event...