Exercise 6. Suppose X1 and X2 are independent standard normal random variables. For a constant a let Wi = cos(a)X1 – sin(a)X2 W2 = sin(@)X1 + cos(@)X2 - Show that W and W2 are independent standard normal random variables.
Exercise 6. Suppose X1 and X2 are independent standard normal random variables. For a constant a let Wi = cos(a)X1 – sin(a)X2 W2 = sin(@)X1 + cos(@)X2 - Show that W and W2 are independent standard normal random variables.
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
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![Exercise 6. Suppose X1 and X2 are independent standard normal random
variables. For a constant a let
Wi = cos(a)X1 – sin(a)X2
W2 = sin(a)X1 + cos(a)X2
|3D
Show that W1 and W2 are independent standard normal random variables.
Remark Geometrically the given transformation is just a rotation of the plane
by an angle a. So the conclusion is simply a reflection of the fact that the joint
distribution has circular symmetry; i.e. is invariant under rotations.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F718b1378-40e4-4c32-83bc-211fc46d7de4%2Fcc0327a5-7e10-4cc9-80d9-ec9a4095d003%2Fs793ejq_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Exercise 6. Suppose X1 and X2 are independent standard normal random
variables. For a constant a let
Wi = cos(a)X1 – sin(a)X2
W2 = sin(a)X1 + cos(a)X2
|3D
Show that W1 and W2 are independent standard normal random variables.
Remark Geometrically the given transformation is just a rotation of the plane
by an angle a. So the conclusion is simply a reflection of the fact that the joint
distribution has circular symmetry; i.e. is invariant under rotations.
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