rv X and Y have a joint Gaussian distribution ~ N(µ =[0.5,1.6], Σ a. Where is the centroid of the distribution, i.e., (X,Y) coordinates? b. Are X and Y independent? Explain why or why not = C. What is the standard deviation of X, σx? [0.5 0.2)] 10.2 0.3. d. In the covariance matrix, if 0.5 increased to 1.5, what would happen to the distribution? e. What is cov(X,Y)? f. Sketch the approximate shape of this distribution
rv X and Y have a joint Gaussian distribution ~ N(µ =[0.5,1.6], Σ a. Where is the centroid of the distribution, i.e., (X,Y) coordinates? b. Are X and Y independent? Explain why or why not = C. What is the standard deviation of X, σx? [0.5 0.2)] 10.2 0.3. d. In the covariance matrix, if 0.5 increased to 1.5, what would happen to the distribution? e. What is cov(X,Y)? f. Sketch the approximate shape of this distribution
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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![rv X and Y have a joint Gaussian distribution ~ N(µ =[0.5,1.6], Σ
a. Where is the centroid of the distribution, i.e., (X,Y) coordinates?
b. Are X and Y independent? Explain why or why not
=
C.
What is the standard deviation of X, σx?
[0.5 0.2)]
10.2 0.3.
d. In the covariance matrix, if 0.5 increased to 1.5, what would happen to the distribution?
e.
What is cov(X,Y)?
f.
Sketch the approximate shape of this distribution](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F0410076e-e393-43c8-aa6b-10916c99abbf%2F29ca0cee-d7e1-422e-83a5-494c4d7caadb%2Fov65csi_processed.jpeg&w=3840&q=75)
Transcribed Image Text:rv X and Y have a joint Gaussian distribution ~ N(µ =[0.5,1.6], Σ
a. Where is the centroid of the distribution, i.e., (X,Y) coordinates?
b. Are X and Y independent? Explain why or why not
=
C.
What is the standard deviation of X, σx?
[0.5 0.2)]
10.2 0.3.
d. In the covariance matrix, if 0.5 increased to 1.5, what would happen to the distribution?
e.
What is cov(X,Y)?
f.
Sketch the approximate shape of this distribution
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