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(This example is a puzzle that doesn't use the theory of this section.) We've discussed how to generate a random variable with a specified distribution starting with a uniformly distributed random variable. Suppose instead that we would like to generate Bernoulli random variables with parameter p = 0.5 using flips of a biased coin. That is, suppose that the probability the coin shows H (for heads) is a, where a is some number that might not be precisely known. Explain how this coin can be used to generate independent Bernoulli random variables with p = 0.5.

(This example is a puzzle that doesn't use the theory of this section.) We've discussed how to generate a random variable with a specified distribution starting with a uniformly distributed random variable. Suppose instead that we would like to generate Bernoulli random variables with parameter p = 0.5 using flips of a biased coin. That is, suppose that the probability the coin shows H (for heads) is a, where a is some number that might not be precisely known. Explain how this coin can be used to generate independent Bernoulli random variables with p = 0.5.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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(This example is a puzzle that doesn't use the theory of this section.) We've discussed how to generate a random variable with a specified distribution starting with a uniformly distributed random variable. Suppose instead that we would like to generate Bernoulli random variables with parameter p = 0.5 using flips of a biased coin. That is, suppose that the probability the coin shows H (for heads) is a, where a is some number that might not be precisely known. Explain how this coin can be used to generate independent Bernoulli random variables with p = 0.5.
Transcribed Image Text:(This example is a puzzle that doesn't use the theory of this section.) We've discussed how to generate a random variable with a specified distribution starting with a uniformly distributed random variable. Suppose instead that we would like to generate Bernoulli random variables with parameter p = 0.5 using flips of a biased coin. That is, suppose that the probability the coin shows H (for heads) is a, where a is some number that might not be precisely known. Explain how this coin can be used to generate independent Bernoulli random variables with p = 0.5.
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