Q- If Y1,…,Yn is an i.i.d. random sample from a population with mean μY and variance σ2Y, which of the following is not true?
1) Y1,…,Yn are identically distributed random variables
2) Y1,…,Yn are mutually independent random variables
3) Var(Y¯)=σ2Y
4) E(Y¯)=μY
Q- If Y1,…,Yn is an i.i.d. random sample from a population with mean μY and variance...
Suppose Y1, Y2, …, Yn are independent and identically distributed random variables from a uniform distribution on [0,k]. a. Determine the density of Y(n) = max(Y1, Y2, …, Yn). b. Compute the bias of the estimator k = Y(n) for estimating k.
Let Y1, Y2, . .. , Yn be independent and identically distributed random variables such that for 0 < p < 1, P(Yi = 1) = p and P(H = 0) = q = 1-p. (Such random variables are called Bernoulli random variables.) a Find the moment-generating function for the Bernoulli random variable Y b Find the moment-generating function for W = Yit Ye+ … + . c What is the distribution of W? 1.
1. Let X1, ..., Xn, Y1, ..., Yn be mutually independent random variables, and Z = + Li-i XiYi. Suppose for each i E {1,...,n}, X; ~ Bernoulli(p), Y; ~ Binomial(n,p). What is Var[Z]?
Exercise 7. Let Xi, X2, . . . be independent, identically distributed rundorn variables uithEX and Var(X) 9, and let Yǐ = Xi/2. We also define Tn and An to be the sum and the sample mean, respectively, of the random variablesy, ,Y,- 1) Evaluate the mean and variance of Yn, T,, and A (2) Does Yn converge in probability? If so, to what value? 3) Does Tn converge in probability? If so, to what value? (4) Does An converge...
Let Y, Y2, ..., Yn be n i.i.d random variables drawn from the population distribution of Y-(My, oy). Suppose we want to estimate My and we are asked to choose between two possible estimators of Wy: (1)Y, and (2) Y = (x + 3) (a) Show both estimators are unbiased (2 points) (b) Derive the variance of both estimators and discuss which estimator is more efficient (3 points)
Let Y1, Y2, , Yn be independent, normal random variables, each with mean μ and variance σ^2. (a) Find the density function of f Y(u) = (b) If σ^2 = 25 and n = 9, what is the probability that the sample mean, Y, takes on a value that is within one unit of the population mean, μ? That is, find P(|Y − μ| ≤ 1). (Round your answer to four decimal places.) P(|Y − μ| ≤ 1) = (c)...
8.5 Random variables Y1,... , Yn have a joint normal distribution with mean 0 if there exist independent random variables Xi,... , Xn, each normal mearn 0, variance 1, and constants aij such that Y aiX1+.. +ainXn Let Xt be a standard Brownian motion. Let s1 s2 sn. Explain why it follows from the definition of a Brownian motion that Xs1,... , Xs, have a joint normal distribution. 8.5 Random variables Y1,... , Yn have a joint normal distribution with...
Suppose that Y1 , Y2 ,..., Yn denote a random sample of size n from a normal population with mean μ and variance 2 . Problem # 2: Suppose that Y , Y,,...,Y, denote a random sample of size n from a normal population with mean u and variance o . Then it can be shown that (n-1)S2 p_has a chi-square distribution with (n-1) degrees of freedom. o2 a. Show that S2 is an unbiased estimator of o. b....
Let X1,X2,...,Xn be an independent and identically distributed (i.i.d.) random sample of Beta distribution with parameters α = 2 and β = 1, i.e., with probability density function fX(x) = 2x for x ∈ (0,1). Find the probability density function of the first and last order statistics Y1 and Yn.
Let Y1, Y2, . . . , Yn be independent random variables with Exponential distribution with mean β. Let Y(n) = max(Y1,Y2,...,Yn) and Y(1) = min(Y1,Y2,...,Yn). Find the probability P(Y(1) > y1,Y(n) < yn).