(1) Consider X that follows the Bernoulli distribution with
success probability 1/4, that is, P(X =...
(1) Consider X that follows the Bernoulli distribution with
success probability 1/4, that is, P(X = 1) = 1/4 and P(X = 0) =
3/4. Find the probability mass function of Y , when Y = X4 . Find
the second moment of Y . (2) If X ∼ binomial(10, 1/2), then use the
binomial probability table (Table A.1 in the textbook) to find out
the following probabilities: P(X = 5), P(2.9 ≤ X ≤ 4.9) (3) A deck
of...
X, Y and Z are Bernoulli random variables with the following
joint distribution:
P(x, y, z)...
X, Y and Z are Bernoulli random variables with the following
joint distribution:
P(x, y, z) =
.2 if (x, y, z) = (0, 0, 0)
.1 if (x, y, z) = (0, 0, 1)
0 if (x, y, z) = (0, 1, 0)
.1 if (x, y, z) = (0, 1, 1)
.1 if (x, y, z) = (1, 0, 0)
0 if (x, y, z) = (1, 0, 1)
.2 if (x, y, z) = (1, 1, 0)...
(1 point) A Bernoulli differential equation is one of the
form
dydx+P(x)y=Q(x)yn (∗)
Observe that, if n=0...
(1 point) A Bernoulli differential equation is one of the
form
dydx+P(x)y=Q(x)yn (∗)
Observe that, if n=0 or 1, the Bernoulli equation is linear. For
other values of n, the substitution u=y1−n transforms the Bernoulli
equation into the linear equation
dudx+(1−n)P(x)u=(1−n)Q(x).dudx+(1−n)P(x)u=(1−n)Q(x).
Consider the initial value problem
y′=−y(1+9xy3), y(0)=−3.
(a) This differential equation can be written in the form (∗)
with
P(x)= ,
Q(x)= , and
n=.
(b) The substitution u= will transform it into the linear
equation
dudx+ u= .
(c) Using...
Let X_1,…, X_n be a random sample from the Bernoulli
distribution, say P[X=1]=θ=1-P[X=0].
and
Cramer Rao Lower...
Let X_1,…, X_n be a random sample from the Bernoulli
distribution, say P[X=1]=θ=1-P[X=0].
and
Cramer Rao Lower Bound of θ(1-θ)
=((1-2θ)^2 θ(1-θ))/n
Find the UMVUE of θ(1-θ) if such exists.
can you proof [part (b) ] using (Leehmann Scheffe
Theorem step by step solution) to proof
[∑X1-nXbar^2 ]/(n-1) is the umvue , I have the key
solution below
x is complete and sufficient.
S^2=∑ [X1-Xbar ]^2/(n-1) is unbiased estimator of θ(1-θ) since
the sample variance is an unbiased estimator of the...
Let X1, . . . , X10 be iid Bernoulli(p),
and let the prior distribution of...
Let X1, . . . , X10 be iid Bernoulli(p),
and let the prior distribution of p be uniform [0, 1]. Find the
Bayesian estimator of p given X1, . . . ,
X10, assuming a mean square loss function.
A Bernoulli differential equation is one of the form
dy/dx+P(x)y=Q(x)y^n (∗)
Observe that, if n=0 or...
A Bernoulli differential equation is one of the form
dy/dx+P(x)y=Q(x)y^n (∗)
Observe that, if n=0 or 1, the Bernoulli equation is linear. For
other values of n, the substitution u=y^(1−n) transforms the
Bernoulli equation into the linear equation
du/dx+(1−n)P(x)u=(1−n)Q(x).
Consider the initial value problem xy′+y=−8xy^2, y(1)=−1.
(a) This differential equation can be written in the form (∗)
with P(x)=_____, Q(x)=_____, and n=_____.
(b) The substitution u=_____ will transform it into the linear
equation du/dx+______u=_____.
(c) Using the substitution in part...
Consider the family of distributions with pmf pX(x) = p if x =
−1, 2p if...
Consider the family of distributions with pmf pX(x) = p if x =
−1, 2p if x = 0, 1 − 3p if x = 1 . Here p is an unknown parameter,
and 0 ≤ p ≤ 1/3. Let X1, X2, . . . , Xn be iid with common pmf a
member of this family. Consider the statistics A = the number of i
with Xi = −1, B = the number of i with Xi = 0,...
A Bernoulli differential equation is one of the form
dxdy+P(x)y=Q(x)yn
Observe that, if n=0 or 1,...
A Bernoulli differential equation is one of the form
dxdy+P(x)y=Q(x)yn
Observe that, if n=0 or 1, the Bernoulli equation is linear. For
other values of n, the substitution u=y^(1−n) transforms the
Bernoulli equation into the linear equation
du/dx+(1−n)P(x)u=(1−n)Q(x)
Use an appropriate substitution to solve the equation
y'−(3/x)y=y^4/x^2 and find the solution that satisfies y(1)=1
Consider a random variable X with the following probability
distribution:
P(X=0) = 0.08, P(X=1) = 0.22,...
Consider a random variable X with the following probability
distribution:
P(X=0) = 0.08, P(X=1) = 0.22,
P(X=2) = 0.25, P(X=3) = 0.25,
P(X=4) = 0.15, P(X=5) =
0.05
Find the expected value of X and the standard deviation of
X.