Suppose that (X,Y) has a bivariate normal distribution with parameters μ x , μ y , σ x , σ , ρ . a. Show that ( X − μ x σ x , Y − μ y σ y ) has a bivariate normal distribution with parameters 0,1,0,1, ρ . b. What is the joint distribution of ( a X + b , c Y + d ) .
Suppose that (X,Y) has a bivariate normal distribution with parameters μ x , μ y , σ x , σ , ρ . a. Show that ( X − μ x σ x , Y − μ y σ y ) has a bivariate normal distribution with parameters 0,1,0,1, ρ . b. What is the joint distribution of ( a X + b , c Y + d ) .
Solution Summary: The author explains the bivariate normal distribution of the given function. The joint density function mathrmfleft is a random variable.
Suppose that (X,Y) has a bivariate normal distribution with parameters
μ
x
,
μ
y
,
σ
x
,
σ
,
ρ
.
a. Show that
(
X
−
μ
x
σ
x
,
Y
−
μ
y
σ
y
)
has a bivariate normal distribution with parameters 0,1,0,1,
ρ
.
b. What is the joint distribution of
(
a
X
+
b
,
c
Y
+
d
)
.
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.
Suppose X, and X, have a bivariate normal distribution. Then, the condition distribution
of X, given X, = x, follows a normal distribution with variance,
o:(1-p)'
of(1-p²)
0,(1-p²)
a)
b)
c)
d)
0,(1-p)
If the random variable X follows the uniform distribution U= (0,1)
What is the distribution of the random variable Y= -2lnX. Show its limits.
Let Y, represent the th normal population with unknown mean 4, and unknown variance
of for i=1,2. Consider independent random samples, Y₁, Y2. Yin, of size n₁, from
the ith population with sample mean Y, and sample variance S² = ₁₁-1(Y₁-₁².
j=1
(g) For non-zero constants a's, what is the distribution of U₂ = a₁Y₁-a₂Y₂? State all
the relevant parameters of the distribution.
(h) Find the standard error of U₂ in part (g), assuming that of = 0² = 0².
(i) Discuss how the distribution of Y₁ - ₂ can be used to test the equality of the two
population means, #₁ and μ2, when o² = 0 = 0² is known.
(j) Define appropriate rejection regions, in terms of Y₁ - Y2, for testing Ho: #₁ = 2
against a two-sided alternative hypothesis at the a level of significance.
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