Square of a standard normal: let X1, ..., Xn ~ X be i.i.d. standard normal variables....
1) Let X and Y be random variables. Show that Cov( X + Y, X-Y) Var(X)--Var(Y) without appealing to the general formulas for the covariance of the linear combinations of sets of random variables; use the basic identity Cov(Z1,22)-E[Z1Z2]- E[Z1 E[Z2, valid for any two random variables, and the properties of the expected value 2) Let X be the normal random variable with zero mean and standard deviation Let ?(t) be the distribution function of the standard normal random variable....
Please answer question (a) X1 - X X2 – Å a. Let X1, ..., Xn i.i.d. random variables with X; ~ N(u, o). Express the vector in the | Xn – form AX and find its mean and variance covariance matrix. Show some typical elements of the vari- ance covariance matrix. b. Refer to question (a). The sample variance is given by S2 = n11 21–1(X; – X)2, which can be ex- pressed as S2 = n1X'(I – 111')X (why?)....
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,..., Xn be i.i.d. random variables. Find
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
Please show step by step solution. 7. Let X1, X2, ..., Xn be i.i.d. random variables drawn from a N(u,0%). Show that the Sample Variance (52) and the Maximum Likelihood Estimator (S) of o2 are both Consistent Estimators for o?. S2 27=2(X-X)2 and S 21-2(X;-) n-1 n (n-1)S Hint: has a Chi-Square Distr. with (n − 1) degrees of freedom. E(x{n-1)) = n-1,V(xin-1)) = 2(n − 1)
39*. Let X1,... ,Xn be i.i.d. random variables. Find
7. Let X1, X2, ... be an i.i.d. random variables. (a) Show that max(X1,... , X,n)/n >0 in probability if nP(Xn > n) -» 0. (b) Find a random variable Y satisfying nP(Y > n) ->0 and E(Y) = Oo
Let X1, X2, , xn are independent random variables where E(X)-? and Var(X) ?2 for all i = 1, 2, , n. Let X-24-xitx2+--+Xy variables. is the average of those random Find E(X) and Var(X).
Let X1, ..., Xn be a random sample (i.i.d.) from a normal distribution with parameters µ, σ2 . (a) Find the maximum likelihood estimation of µ and σ 2 . (b) Compare your mle of µ and σ 2 with sample mean and sample variance. Are they the same?