A discrete random variable X has probability mass function P() 0.1 0.2 0.2 0.2 0.3 Use...
#3.7 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....
2. A discrete random variable X can be 2, 8, 10 and 20 and its probabilities are 0.3, 0.4, 0.1 and 0.2, respectively. Drive the inverse-transform algorithm for the distribution. 2. A discrete random variable X can be 2, 8, 10 and 20 and its probabilities are 0.3, 0.4, 0.1 and 0.2, respectively. Drive the inverse-transform algorithm for the distribution
2) Consider a random variable with the following probability distribution: P(X = 0) = 0.1, P(X=1) =0.2, P(X=2) = 0.3, P(X=3) = 0.3, and P(X=4)= 0.1. A. Generate 400 values of this random variable with the given probability distribution using simulation. B. Compare the distribution of simulated values to the given probability distribution. Is the simulated distribution indicative of the given probability distribution? Explain why or why not. C. Compute the mean and standard deviation of the distribution of simulated...
5.Consider a discrete random variable X with the probability mass function xp(x) Consider Y-g(X) 0.2 0.4 0.3 0.1 a)Find the probability distribution of Y b) Find the expected value of Y, E(Y) Does μ Y equal to g(μx)? 4
Suppose a discrete random variable X has the following probability distribution () 0.1 0.1 0.2 0.6 Find the CDF of X and write it as a piecewise function.
5 Consider a discrete random variable X with the probability mass function rp(x) Consider Y = g( X ) =- 0.2 0.4 0.3 0.1 a) Find the probability distribution of Y. b Find the expected value of Y, E(Y). Does μ Y equal to g(Hy )? 4
2) Consider a random variable with the following probability distribution: P(X-0)-0., Px-1)-0.2, PX-2)-0.3, PX-3) -0.3, and PX-4)-0.1 A. Generate 400 values of this random variable with the given probability distribution using simulation. B. Compare the distribution of simulated values to the given probability distribution. Is the simulated distribution indicative of the given probability distribution? Explain why or why not. C. Compute the mean and standard deviation of the distribution of simulated values. How do these summary measures compare to the...
Explain why the probability mass function P(X = 1000) = 0.1, P(X = 1500) = 0.2, P(X = 2000) = 0.3, P(X = 2500) = 0.3, P(X = 3000) = 0.1 is not practical as a distribution for the number of phone calls to a help-desk call center during a day
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.
The discrete random variable X has the following probability mass function: f(x) = kx, for the values of x = 2,4,5 and 6 only. Find the i. value of k. ii. construct the probability distribution of X iii. expected value and standard deviation X