
Gibbs Sampling Concepts and Applications

Interactive Video
•
Mathematics
•
11th - 12th Grade
•
Hard

Thomas White
FREE Resource
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7 questions
Show all answers
1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary use case for Gibbs Sampling?
Sampling from single-dimensional distributions
Sampling from multivariate distributions
Sampling from discrete distributions
Sampling from uniform distributions
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In the two-dimensional normal distribution example, what is the mean vector?
(1, 0)
(0.5, 0.5)
(0, 0)
(1, 1)
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is sampling from the joint distribution considered difficult?
The equations are always unknown
It involves simultaneous sampling of multiple variables
It is only applicable to single-dimensional distributions
It requires high computational power
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the first step in the Gibbs Sampling algorithm?
Sample a new value for y
Initialize x and y
Fix the covariance matrix
Calculate the joint distribution
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does Gibbs Sampling achieve convergence?
By adjusting the covariance matrix
By iterating over conditional distributions
By sampling all variables simultaneously
By using a fixed number of samples
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is a variation of Gibbs Sampling?
Using a different covariance matrix
Sampling in a fixed order
Ignoring conditional distributions
Sampling from a single variable
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is a potential pitfall of Gibbs Sampling?
It cannot handle high-dimensional data
It always converges too quickly
It may get stuck in low or high probability regions
It requires a large number of samples
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