Let
X1,X2,...,Xn
be i.i.d. (independent and identically distributed) from the
Bernoulli distribution
f(x)=p^x(1-p)^1-x,
x=0,1,p∈(0,1) where p...
Let
X1,X2,...,Xn
be i.i.d. (independent and identically distributed) from the
Bernoulli distribution
f(x)=p^x(1-p)^1-x,
x=0,1,p∈(0,1) where p is unknown parameter. Find the UMVUE of
p parameter and calculate MSE (Mean Square Error) of this UMVUE
estimator.
1. Let X1, X2 be i.i.d with this distribution: f(x) = 3e cx, x ≥
0 a. Find the value of c
b. Recognize this as a famous distribution that we’ve learned in
class. Using your knowledge of this distribution, find the t such
that P(X1 > t) = 0.98.
c. Let M = max(X1, X2). Find P(M < 10)
Problem 1 Let X1, X2, . . . , Xn be independent Uniform(0,1)
random variables. (
a) Compute the cdf of Y := min(X1, . . . , Xn).
(b) Use (a) to compute the pdf of Y .
(c) Find E(Y ).
Let X1 and X2 be independent identically
distributed random variables with pmf p(0) = 1/4, p(1) = 1/2, p(2)
= 1/4
(a) What is the probability mass function (pmf) of X1
+ X2?
(b) What is the probability mass function (pmf) of
X(2) = max{X1, X2}?
(c) What is the MGF of X1?
(d) What is the MGF of X1 + X2
Let X1 and X2 be independent identically distributed random
variables with pmf p(0) = 1/4, p(1) = 1/2, p(2) = 1/4
(a) What is the probability mass function (pmf) of X1 + X2?
(b) What is the probability mass function (pmf) of X(2) =
max{X1, X2}?
(c) What is the MGF of X1?
(d) What is the MGF of X1 + X2? (Note: The formulas we did were
for the continuous case, so they don’t directly apply here, but you...
Let X1, X2, . . . be a sequence of independent and identically
distributed random variables where the distribution is given by the
so-called zero-truncated Poisson distribution with probability mass
function; P(X = x) = λx/ (x!(eλ − 1)), x = 1, 2,
3...
Let N ∼ Binomial(n, 1−e^−λ ) be another random variable that is
independent of the Xi ’s.
1) Show that Y = X1
+X2 + ... + XN has a Poisson distribution
with mean nλ.
Let X1,..., Xn be an i.i.d. sample from a geometric distribution
with parameter p.
U = ( 1, if X1 = 1, 0, if X1 > 1)
find a sufficient statistic T for p.
find E(U|T)
Let X1. . . . Xn be i.i.d f(x; θ) = θ(1 − θ)^x x = 0.. Is there
a function of θ for which there exists an unbiased estimator of θ
whose variance achieves the CRLB? If so, find it
Let X1, X2, · · · , Xn (n ≥ 30)
be i.i.d observations from N(µ1,
σ12 ) and Y1, Y2, · · ·
, Yn be i.i.d observations from N(µ2,
σ22 ). Also assume that X's and Y's are
independent. Suppose that µ1, µ2,
σ12 ,
σ22 are unknown. Find an
approximate 95% confidence interval for
µ1µ2.
2. Let X1, X2, . . . , Xn be independent, uniformly distributed
random variables on the interval [0, θ]. (a) Find the pdf of X(j) ,
the j th order statistic. (b) Use the result from (a) to find
E(X(j)). (c) Use the result from (b) to find E(X(j)−X(j−1)), the
mean difference between two successive order statistics. (d)
Suppose that n = 10, and X1, . . . , X10 represents the waiting
times that the n = 10...
Let X = ( X1, X2, X3, ,,,, Xn ) is iid,
f(x, a, b) = 1/ab * (x/a)^{(1-b)/b} 0 <= x <= a ,,,,, b
< 1
then, find a two dimensional sufficient statistic for (a, b)