Let λ >0 and suppose that X1,X2,...,Xn be i.i.d. random variables with Xi∼Exp(λ). Find the PDF of X1+···+Xn. Use convolution formula and prove by induction
Let λ >0 and suppose that X1,X2,...,Xn be i.i.d. random variables with Xi∼Exp(λ). Find the PDF...
Let X1, , xn be i.i.d. Jointly continuous randorn variables. Find the pdf of Y. , X, and Y) = min(Xi, Using your formula, write down the pdfs of Y and Y2 when Xi ~ Exp(X). Can you identify the distribution of Y2?
Central Limit Theorem: let x1,x2,...,xn be I.I.D. random variables with E(xi)= U Var(xi)= (sigma)^2 defind Z= x1+x2+...+xn the distribution of Z converges to a gaussian distribution P(Z<=z)=1-Q((z-Uz)/(sigma)^2) Use MATLAB to prove the central limit theorem. To achieve this, you will need to generate N random variables (I.I.D. with the distribution of your choice) and show that the distribution of the sum approaches a Guassian distribution. Plot the distribution and matlab code. Hint: you may find the hist() function helpful
Exercise 8.41. The random variables X1,..., Xn are i.i.d. We also know that ElXl] = 0. EĮKY = a and Elx?| = b. Let Xn-Xi+n+Xn. Find the third moment of Xn Exercise 8.41. The random variables X1,..., Xn are i.i.d. We also know that ElXl] = 0. EĮKY = a and Elx?| = b. Let Xn-Xi+n+Xn. Find the third moment of Xn
(5) Let X1,X2,,Xn be independent identically distributed (i.i.d.) random variables from 1.1 U(0,1). Denote V max{Xi,..., Xn) and W min{Xi,..., Xn] (a) Find the distributions and the densities and the distributions of each of V and W. (b) Find E(V) and E(W) (5) Let X1,X2,,Xn be independent identically distributed (i.i.d.) random variables from 1.1 U(0,1). Denote V max{Xi,..., Xn) and W min{Xi,..., Xn] (a) Find the distributions and the densities and the distributions of each of V and W. (b)...
Exercise l (Sum of 1.1.d. Exp is Erlang. Let Xi, X2, , Xn ~ Exp(λ) be independent exponential RVs. m Show that fx +x2 (z) = λ2ze-Azi (z 0). (ii) snow that fA+A+x, (z)= 2jaz2e-λΖ1(Z20). (iii) Let Sn-X1 + X2+ + Xn. Use induction to show that Sn ~ Erlang(n, λ), that is, Ctrl+S Ís (z) =-(n-1)!
Let X1,..., Xn be i.i.d. random variables. Find
3. Suppose that X1, X2, X3 be i.i.d. random variables with P(Xi 0) 2/5 and P(X 1) 3/5. Find the MGFof X, + X2 + X 3. 3. Suppose that X1, X2, X3 be i.i.d. random variables with P(Xi 0) 2/5 and P(X 1) 3/5. Find the MGFof X, + X2 + X 3.
39*. Let X1,... ,Xn be i.i.d. random variables. Find
Answer the following questions: a. Let X1, X2, . . . , Xn be i.i.d. random vectors (a random sample) from Np(μ1, Σ). Find the distribution of X ̄ . Note: X ̄ = 1/n Xi . b. Refer to question (a). Consider the following two random variables: Q1 = 1′X ̄/1'1 and Q2 = 1′Σ−1X ̄/1′Σ−11 ̄ . Find the mean and variance of Q1 and Q2 .
Let X1, X2, X3, . be a sequence of i.i.d. Uniform(0,1) random variables. Define the sequence Yn as Ymin(X1, X2,,Xn) Prove the following convergence results independently (i.e, do not conclude the weaker convergence modes from the stronger ones). d Yn 0. a. P b.Y 0. L 0, for all r 1 Yn C. a.s d. Y 0. Let X1, X2, X3, . be a sequence of i.i.d. Uniform(0,1) random variables. Define the sequence Yn as Ymin(X1, X2,,Xn) Prove the following...