16. In a Poisson Distribution, the mean and variance are equal. a) True b) False
Elementary Linear Algebra (MindTap Course List)
8th Edition
ISBN:9781305658004
Author:Ron Larson
Publisher:Ron Larson
Chapter2: Matrices
Section2.5: Markov Chain
Problem 55E
Related questions
Question
solve question 16 with complete explanation
![12. The events having no experimental outcomes in common is called:
a) Equally likely events e
b) Exhaustive events
c) Mutually exclusive events e
d) Independent events
13. When the occurrence of one event has no effect on the probability of the
occurrence of another event, the events are called:
a) Independent e
b) Dependent e
c) Mutually exclusive e
d) Equally likelye
14. The probability density function of a Markov process is
a) p(x1,x2,x3..xn) = p(x1)p(x2/x1)p(x3/x2)...p(xn/xn-1)e
b) p(x1,x2,x3.xn) = p(x1)p(x1/x2)p(x2/x3)..p(xn-1/xn)-
c) p(x1,x2,x3..xn) = p(x1)p(x2)p(x3)..p(xn)e
d) p(x1,x2,x3...xn) = p(x1)p(x2 *x1)p(x3*x2)...p(xn*xn-1)e
..xn) =
.....
15. The discrete probability distribution in which the outcome is very small with a
very small period of time is classified as «
a) Posterior distribution
b) Cumulative distributione
c) Normal distributione
d) Poisson distributione
16. In a Poisson Distribution, the mean and variance are equal.
a) True
b) False](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F13663ee8-7c93-499a-9873-820a8b57672d%2Fb151b3d7-2534-4f4e-821e-3355b11fb4b2%2Fu31rf1gx_processed.png&w=3840&q=75)
Transcribed Image Text:12. The events having no experimental outcomes in common is called:
a) Equally likely events e
b) Exhaustive events
c) Mutually exclusive events e
d) Independent events
13. When the occurrence of one event has no effect on the probability of the
occurrence of another event, the events are called:
a) Independent e
b) Dependent e
c) Mutually exclusive e
d) Equally likelye
14. The probability density function of a Markov process is
a) p(x1,x2,x3..xn) = p(x1)p(x2/x1)p(x3/x2)...p(xn/xn-1)e
b) p(x1,x2,x3.xn) = p(x1)p(x1/x2)p(x2/x3)..p(xn-1/xn)-
c) p(x1,x2,x3..xn) = p(x1)p(x2)p(x3)..p(xn)e
d) p(x1,x2,x3...xn) = p(x1)p(x2 *x1)p(x3*x2)...p(xn*xn-1)e
..xn) =
.....
15. The discrete probability distribution in which the outcome is very small with a
very small period of time is classified as «
a) Posterior distribution
b) Cumulative distributione
c) Normal distributione
d) Poisson distributione
16. In a Poisson Distribution, the mean and variance are equal.
a) True
b) False
Expert Solution
![](/static/compass_v2/shared-icons/check-mark.png)
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
Step by step
Solved in 2 steps with 2 images
![Blurred answer](/static/compass_v2/solution-images/blurred-answer.jpg)
Recommended textbooks for you
![Elementary Linear Algebra (MindTap Course List)](https://www.bartleby.com/isbn_cover_images/9781305658004/9781305658004_smallCoverImage.gif)
Elementary Linear Algebra (MindTap Course List)
Algebra
ISBN:
9781305658004
Author:
Ron Larson
Publisher:
Cengage Learning
![Linear Algebra: A Modern Introduction](https://www.bartleby.com/isbn_cover_images/9781285463247/9781285463247_smallCoverImage.gif)
Linear Algebra: A Modern Introduction
Algebra
ISBN:
9781285463247
Author:
David Poole
Publisher:
Cengage Learning
![Elementary Linear Algebra (MindTap Course List)](https://www.bartleby.com/isbn_cover_images/9781305658004/9781305658004_smallCoverImage.gif)
Elementary Linear Algebra (MindTap Course List)
Algebra
ISBN:
9781305658004
Author:
Ron Larson
Publisher:
Cengage Learning
![Linear Algebra: A Modern Introduction](https://www.bartleby.com/isbn_cover_images/9781285463247/9781285463247_smallCoverImage.gif)
Linear Algebra: A Modern Introduction
Algebra
ISBN:
9781285463247
Author:
David Poole
Publisher:
Cengage Learning