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- Let X₁, X₂, X3,..., Xn denote a random sample of size n from the population distributed with the following probability density function: ((0+1)xº, = {CO₂ + 0, f(x; 0) = Find the maximum likelihood estimator (MLE) of 0. if 0 < x < 1 elsewhereThe continuous random variable Y has the following pdf: 1- y?, 0Let f, g be probability densities such supp(f) c supp(g). show yes X1, ... , Xn X1,..., X, iid. L(g) then f(X;) W; = g(X;) is hopeful 1. Argue why the weights need to be re-normalized even when the normalization constants of the densities f and g are known.1. Let X have the probability density function f(x) = cx(1-2) for 0≤x≤ 1 and f(x) = 0 otherwise. (a) Show that c = 6. (b) Find the cumulative distribution function F(x) = P(X ≤ z). (c) Calculate P(.1 < X <5). (d) Find the mean, variance and standard deviation of X.Suppose an industry produced a particular type of metal mixture up to 1 ton a day. Due to technical difficulties or system breakdowns, the actual amount produced by the industry is Y, a random variable which has the following Probability density function: f(y) = √2y 0Let random sample of n observations from each of the distributions: a. Poisson distribution with parameter θ. b. f(x, θ) = (1/ θ) e-x/θ , 0 < x. In each case find the Minimum Variance Estimator of θ and prove its efficiency.Let Y denote a random variable with the following cumulative distribution function. if y 1. F(y) : In(4) a. Find the PDF, ƒ(y). b. Evaluate P(Y = 0.5). c. Evaluate P(Y 0.4). d. Evaluate P(Y < 1).Let X be a random variable with CDF x > 1 Fx(x) = 0 < x < 1 %3D x < 0 a. What kind of random variable is X: discrete, continuous, or mixed? b. Find the PDF of X, fx(x). c. Find E(ex).Recommended textbooks for youA First Course in Probability (10th Edition)ProbabilityISBN:9780134753119Author:Sheldon RossPublisher:PEARSONA First Course in Probability (10th Edition)ProbabilityISBN:9780134753119Author:Sheldon RossPublisher:PEARSON