Suppose that Y is a normal random variable with mean μ and variance σ 2 , and suppose also that the conditional distribution of X, given that Y = y , is normal with mean y and variance 1. a. Argue that the joint distribution of X, Y is the same as that of Y + Z , Y when Z is a standard normal random variable that is independent of Y. b. Use the result of part (a) to argue that X, Y has a bivariate normal distribution . c. Find E [ X ] , var ( X ) , and C o r r ( X , Y ) . d. Find E [ Y | X = x ] . e. What is the conditional distribution of Y given that X = x ?
Suppose that Y is a normal random variable with mean μ and variance σ 2 , and suppose also that the conditional distribution of X, given that Y = y , is normal with mean y and variance 1. a. Argue that the joint distribution of X, Y is the same as that of Y + Z , Y when Z is a standard normal random variable that is independent of Y. b. Use the result of part (a) to argue that X, Y has a bivariate normal distribution . c. Find E [ X ] , var ( X ) , and C o r r ( X , Y ) . d. Find E [ Y | X = x ] . e. What is the conditional distribution of Y given that X = x ?
Solution Summary: The author explains how the joint distribution of mathrmX,mây of the given random variable is calculated.
Suppose that Y is a normal random variable with mean
μ
and variance
σ
2
, and suppose also that the conditional distribution of X, given that
Y
=
y
, is normal with mean y and variance 1.
a. Argue that the joint distribution of X, Y is the same as that of
Y
+
Z
, Y when Z is a standard normal random variable that is independent of Y.
b. Use the result of part (a) to argue that X, Y has a bivariate normal distribution.
c. Find
E
[
X
]
,
var
(
X
)
, and
C
o
r
r
(
X
,
Y
)
.
d. Find
E
[
Y
|
X
=
x
]
.
e. What is the conditional distribution of Y given that
X
=
x
?
Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.
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