Question

Let X1,X2,…,Xn iid∼Unif(0,b) be n i.i.d. uniform random variables on the interval [0,b] for some positive...

Let X1,X2,…,Xn iid∼Unif(0,b) be n i.i.d. uniform random variables on the interval [0,b] for some positive b. Suppose n is small (i.e. n<30) so that the central limit theorem is not justified.

Find an upper bound on the probability that the sample mean is “far away" from the expectation (the true mean) of X. More specifically, find the respective upper bounds given by the Chebyshev and Hoeffding inequalities on the following probability:

P(≥|Xn−E[X]|≥ c σ /√n)where σ2=VarXi

for c=2 and c=6. Each answer is numerical.

Homework Answers

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Let X1,…, Xn be a sample of iid N(0, ?)random variables with Θ = ℝ. a)...
Let X1,…, Xn be a sample of iid N(0, ?)random variables with Θ = ℝ. a) Show that T = (1/?)∑ni=1 Xi2 is a pivotal quantity. b) Determine an exact (1 − ?) × 100% confidence interval for ? based on T. c) Determine an exact (1 − ?) × 100% upper-bound confidence interval for ? based on T.
For X1, ..., Xn iid Unif(0, 1): a) ShowX(j) ∼Beta(j,n+1−j) b)Find the joint pdf between X(1)...
For X1, ..., Xn iid Unif(0, 1): a) ShowX(j) ∼Beta(j,n+1−j) b)Find the joint pdf between X(1) and X(n) c) Show the conditional pdf X(1)|X(n) ∼ X(n)Beta(1, n − 1
For X1, ..., Xn iid Unif(0, 1): a) Show the conditional pdf X(i)|X(j) ∼ X(j)Beta(i, j...
For X1, ..., Xn iid Unif(0, 1): a) Show the conditional pdf X(i)|X(j) ∼ X(j)Beta(i, j − i) b Let n=5, find the joint pdf between X(2) and X(4).
Let X1, X2, . . . , Xn be iid random variables with pdf f(x|θ) =...
Let X1, X2, . . . , Xn be iid random variables with pdf f(x|θ) = θx^(θ−1) , 0 < x < 1, θ > 0. Is there an unbiased estimator of some function γ(θ), whose variance attains the Cramer-Rao lower bound?
Let X1,…, Xn be a sample of iid U[?, 1] random variables with Θ = (−∞,...
Let X1,…, Xn be a sample of iid U[?, 1] random variables with Θ = (−∞, 1]. a) Show that T = (1−X(1) )/(1−?) is a pivotal quantity. b) Determine an exact (1 − ?) × 100% confidence interval for ? based on T. c) Determine an exact (1 − ?) × 100% upper-bound confidence interval for ? based on T.
Let X1, X2, . . . , Xn be iid exponential random variables with unknown mean...
Let X1, X2, . . . , Xn be iid exponential random variables with unknown mean β. (1) Find the maximum likelihood estimator of β. (2) Determine whether the maximum likelihood estimator is unbiased for β. (3) Find the mean squared error of the maximum likelihood estimator of β. (4) Find the Cramer-Rao lower bound for the variances of unbiased estimators of β. (5) What is the UMVUE (uniformly minimum variance unbiased estimator) of β? What is your reason? (6)...
X1, X2,...Xn are iid random variables from a U(0,b) distribution. Which estimator is an unbiased estimator...
X1, X2,...Xn are iid random variables from a U(0,b) distribution. Which estimator is an unbiased estimator for b? 2 X bar n X bar n 1/n (X1squared + X2squared +....Xnsquared) 1/n2(X1squared + X2squared +....Xnsquared)
Let X1, ... , Xn be a sample of iid Beta(4, ?) random variables with ?...
Let X1, ... , Xn be a sample of iid Beta(4, ?) random variables with ? ∈ (0, ∞). a) Determine the likelihood function L(?). b) Use the Fisher–Neyman factorization theorem to determine a sufficient statistic S for ?.
Let X1, ... , Xn be a sample of iid Gamma(?, 1) random variables with ?...
Let X1, ... , Xn be a sample of iid Gamma(?, 1) random variables with ? ∈ (0, ∞). a) Determine the likelihood function L(?). b) Use the Fisher–Neyman factorization theorem to determine a sufficient statistic S for ?.
Let X1,X2...Xn be i.i.d. with N(theta, 1) a) find the CR Rao lower-band for the variance...
Let X1,X2...Xn be i.i.d. with N(theta, 1) a) find the CR Rao lower-band for the variance of an unbiased  estimator of theta b)------------------------------------of theta^2 c)-----------------------------------of P(X>0)