a) i. Correct. Here sample mean is a statistic. And sample mean is based on 10 random variables. If random variables change sample mean will also change for different variables.
a)iii. Correct. Here population mean is 10 therefore our sample mean is not exactly 10 but approximately equal to 10. Because our sample mean statistic is unbiased estimator of population parameter.
a) v. Correct. The variance of
is exactly equal to 1.
var()
= var(x)/n2 =100/102 =100/100 =1
(b)
(c)
(d)
Let Xi, ,Xio be i.i.d. random variables with mean 10, and variance 100. (a) Select all...
Problem 2: Let Xi, X2,..., Xn be i.i.d. random variables with common probability density function 3 -6x21 (i) Calculate the MLE of 0 (ii) Find the limit distribution of Vn(0MLE - 0) and use this result to construct an approximate level 1-α C.I. for θ. [Your confidence interval must have an explicit a form as possible for full credit.] (iii) Calculate μι (0)-E0(Xi) and find a level 1-α C.İ. for μι (0) based on the result in (ii) or by...
Problem 7. Let Xi, X2,..., Xn be i.i.d. (independent and identically distributed) random variables with unknown mean μ and variance σ2. In order to estimate μ and σ from the data we consider the follwing estimates n 1 Show that both these estimates are unbiased. That is, show that E(A)--μ and
Let X1, X2 · · · X10 be i.i.d. random variables. And all of them have the distribution uniform[0, 2]. Please calculate the variance of the 2nd largest number among these X’s.
3. Let Xi,... , Xio be a random sample of size 10 from a gamma distribution with α--3 and β 1/e. The prior distribution of θ is a gamma distribution with α-10 and B-2. Recall that the gamma density is given by elsewhere, (a) Find the posterior distribution of θ (b) If we observe 17, use the mean of the posterior distribution to give a point estimate of θ.
Let Xi, x,, ,X, be independent random variables with mean and variance σ . Let Y1-Y2, , Y, be independent random variables with mhean μ and variance a) Compute the expected value of W b) For what value of a is the variance of W a minimum? σ: Let W-aX + (1-a) Y, where 0 < a < 1.
Let Xi, x,, ,X, be independent random variables with mean and variance σ . Let Y1-Y2, , Y, be independent random...
Let Xi, ..., Xn be random variables with the same mean and with covariance function where |ρ| < 1 . Find the mean and variance of Sn-Xi + . . . + Xn. Assume thatE(X. ) μ and V(X) σ2 for i (1.2. , n}
Let X1, X2, and X3 be uncorrelated random variables, each
with
4. (10 points) Let Xi, X2, and X3 be uncorrelated random variables, each with mean u and variance o2. Find, in terms of u and o2 a) Cov(X+ 2X2, X7t 3X;) b) Cov(Xrt X2, Xi- X2)
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
Problem 5 of 5Sum of random variables Let Mr(μ, σ2) denote the Gaussian (or normal) pdf with Inean ,, and variance σ2, namely, fx (x) = exp ( 2-2 . Let X and Y be two i.i.d. random variables distributed as Gaussian with mean 0 and variance 1. Show that Z-XY is again a Gaussian random variable but with mean 0 and variance 2. Show your full proof with integrals. 2. From above, can you derive what will be the...
1. Let Xi, X2,... be independent random variables each with the standard normal distribution, and for each n 2 0 let Sn-1 Xi. Use importance sampling to obtain good estimates for each of the following probabilities: (a) Pfmaxn<100 Sn> 10; and (b) Pímaxns100 Sn > 30) HINTS: The basic identity of importance sampling implies that d.P n100 where Po is the probability measure under which the random variables Xi, X2,... are independent normals with mean 0 amd variance 1. The...