Gaussian Mixture Models and Functions

Gaussian Mixture Models and Functions

Assessment

Interactive Video

Mathematics, Science, Computers

10th - 12th Grade

Hard

Created by

Patricia Brown

FREE Resource

The video tutorial explains how to simulate a mixture of Gaussian distributions using a coin toss method to select between two Gaussian components. It covers the process of simulating coin tosses, generating Gaussian distributions with specific parameters, and adjusting probability weights to influence the resulting mixture. The tutorial also extends the concept to simulate a mixture of three Gaussian components, demonstrating how to visualize the results using histograms.

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10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of using a coin flip in simulating a mixture of Gaussian distributions?

To calculate the mean of the Gaussian distributions

To set the standard deviation of the distributions

To decide which Gaussian distribution to sample from

To determine the number of samples to generate

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which function is used to simulate the results of a coin flip in R?

rnorm

geom_histogram

sample

table

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What are the mean and standard deviation of the first Gaussian distribution in the simulation?

Mean: 3, SD: 1.5

Mean: 10, SD: 1

Mean: 5, SD: 2

Mean: 0, SD: 1

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How is the resulting mixture of two Gaussians visualized?

Using a line graph

Using a pie chart

Using a histogram

Using a bar chart

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What effect does changing the probability weights have on the Gaussian mixture?

It affects the prominence of each distribution in the mixture

It alters the standard deviation of the distributions

It changes the mean of the distributions

It modifies the number of samples generated

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does a high probability weight indicate about a distribution in the mixture?

The distribution is less important

The distribution is more important

The distribution has a lower standard deviation

The distribution has a higher mean

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How many outcomes are considered in the proportions object for simulating three Gaussian mixtures?

Two outcomes

Three outcomes

Four outcomes

Five outcomes

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