Please answer as neatly as possible.
Much thanks in advance!
I, X2, , X", and Yİ, Y2, X, are independent randonn samples from popula- ). Show 4. Suppose that ...
Suppose that X1, X2,.... Xn and Y1, Y2,.... Yn are independent random samples from populations with the same mean μ and variances σ., and σ2, respectively. That is, x, ~N(μ, σ ) y, ~ N(μ, σ ) 2X + 3Y Show that is a consistent estimator of μ.
In 10. 11, Let X1, X2, . , Xn and Yi, Y2, . . . , Y,, be independent samples from N(μ, σ?) and N(μ, σ), respectively, where μ, σ. ơỈ are unknown. Let ρ-r/of and g m/n, and consider the problem of unbiased estimation of u In 10. 11, Let X1, X2, . , Xn and Yi, Y2, . . . , Y,, be independent samples from N(μ, σ?) and N(μ, σ), respectively, where μ, σ. ơỈ are unknown....
Suppose that independent samples of sizes n1, n2, . . . , nk are taken from each of k normally distributed populations with means μ1,μ2, . . . , μk and common variances, all equal to σ 2. Let Yi j denote the j th observation from population i, for j = 1, 2, . . . , ni and i = 1, 2, . . . , k, and let n = n1 + n2 + ··· + nk...
Suppose that X - (Xi,X2,....X) and Y- (Yi, Y2.., Ym) are random samples from continuous distributions F and G, respectively. Wilcoxon's two-sample test statistic W- W(X, Y) is defined to be re R, is the rank of Y, in the combined sample 2. Show that W can be written as where U is the number of pairs (X,, Y,) with Xi < Y. In other words i if X, < Y, v-ΣΣΙ,j, I,,- where 0 otherwise. Hint: Let Yu), Y2),.......
Suppose Y1, Y2, ... Yn are mutually independent random variables with Y1 ~ N(μ1, (σ1)^2) Y2 ~ N(μ2, (σ2)^2) ... Yn ~ N(μn, (σn)^2) Find the distribution of U=summation(from i=1 to n) ((Yi - μi)/σi)^2 I am not sure where should I start this question, could you please show me the detail that how you do these two parts? thanks :)
σ2). 6. Suppose X1, Yİ, X2, Y2, , Xn, Y, are independent rv's with Xi and Y both N(μ, All parameters μί, 1-1, ,n, and σ2 are unknown. For example, Xi and Yi muay be repeated measurements on a laboratory specimen from the ith individual, with μί representing the amount of some antigen in the specimen; the measuring instrument is inaccurate, with normally distributed errors with constant variability. Let Z, X/V2. (a) Consider the estimate σ2- (b) Show that the...
3. You have two independent random samples: XiXX from a population with mean In and variance σ2 and Y, Y2, , , , , Y,n from a population with mean μ2 and variance σ2. Note that the two populations share a common variance. The two sample variances are Si for the first sample and Si for the second. We know that each of these is an unbiased estimator of the common population variance σ2, we also know that both of...
Let X1 and X2 be independent random variables with means μ1 and μ2, and variances σ21 and σ22, respectively. Find the correlation of X1 and X1 + X2. Note that: The covariance of random variables X; Y is dened by Cov(X; Y ) = E[(X - E(X))(Y - E(Y ))]. The correlation of X; Y is dened by Corr(X; Y ) =Cov(X; Y ) / √ Var(X)Var(Y )
(a) Show that (Xi, X2) has a bivariate normal distribution with means μ1 , μ2, variances 어 and 05, and correlation coefficient ρ if and only if every linear combination c Xc2X2 has a univariate normal distr bution with mean c1μι-c2μ2, and variance c?σ? + c3- +2c1c2ρσ12, where cı and c2 are real constants, not both equal to zero. (b) Let Yİ = Xi/ởi, i = 1,2. Show that Var(Y-Yo) = 2(1-2).
Suppose Y1, Y2, ..., Yn are such that Y; ~ Bernoulli(p) and let X = 2h+Yi. (a) [1 point] Use the distribution of X to show that the method of moments estimator of p is ÔMM = Lizzi. (Work that is unclear or that cannot be followed from step to step will not recieve full credit.) (b) [2 points] Show that the method of moments estimator PMM is a consistent estimator of p. Please show your work to support your...