Pascal: The proverbial coin toss.

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In summary, the question asked whether two sequences of flips of a fair coin had the same probability if they had the same length, and it appears that the answer is no because the examples given do not have independence.
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schema
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I should preface this question by saying that I am a computer science major.

A logic question was posed in an IT class as a challenge. It is extra-curricular and pertains very little to actual subject matter. The question, I assume, was a 'satirical' reference to the pascal language, or perhaps binary code. None of us are math majors, obviously, so hence the challenge. I think our proctor was hinting that we should program a script to solve this, which i intend to do. I just need some guidance in how I find the method in which I can deduce a solution.

We were give 2 sequences of flips (HT) and asked to compare the probabilities of the sequences.I immediately thought of the pascal triangle, which i think is a step in the right direction. However, one of the sequences is repeating while the other is seemingly random:

e.g. HTHTHTHHTHTHTHTHTH
HHHHHHHHTTTTTTTTTT

My question is, do I approach this by mapping this out with pascal triangle and just taking the probability of H in each sequence, or do i need to apply another method to take into account the repeating sequence?
 
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Maybe I don't understand the question. However any specific sequence has a probability (assuming a fair coin) of (1/2)n, where n is the number of tosses.
 
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thank you. that is more direct and simple than I thought.
 
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schema said:
and asked to compare the probabilities of the sequences.

There are other ways to "compare" two probabilities than by computing each probability. We should first determine whether your instructor said to "compare" them or to "compute" them.

Two sequences of independent flips of a fair coin have the same probability if they have the same length.
 
  • #5
Stephen Tashi said:
There are other ways to "compare" two probabilities than by computing each probability. We should first determine whether your instructor said to "compare" them or to "compute" them.

Two sequences of independent flips of a fair coin have the same probability if they have the same length.

The directive was to find "how much more probable" one was to the other. I didn't know if the sequence repetition played a part in how to find the solution.

thank you for the help. this is not my area of expertise.
 
  • #6
mathman said:
Maybe I don't understand the question. However any specific sequence has a probability (assuming a fair coin) of (1/2)n, where n is the number of tosses.

That's assuming independence, which seems questionable in both the examples given.
 
  • #7
awkward said:
That's assuming independence, which seems questionable in both the examples given.

The problem could be investigated not assuming a fair coin or not assuming independence if we take a Bayesian point of view. But if we take that point of view, a problem posed by an instructor not teaching a class in Bayesian statistics probably should be solved by assuming independence and a fair coin.
 

Related to Pascal: The proverbial coin toss.

1. What is "Pascal: The proverbial coin toss"?

"Pascal: The proverbial coin toss" is a thought experiment proposed by the French mathematician and philosopher, Blaise Pascal. It explores the concept of probability and decision-making by using a coin toss as an example.

2. How does the thought experiment work?

The thought experiment goes like this: imagine you have to make a decision with two possible outcomes, and you have no way of knowing which outcome is more likely. In this scenario, Pascal suggests that you should weigh the potential gains and losses of each outcome to make the best decision.

3. What is the significance of this thought experiment?

Pascal's thought experiment highlights the importance of understanding probabilities in decision-making. By considering the potential gains and losses of each outcome, one can make a more informed decision, rather than relying on chance or emotions.

4. Can this thought experiment be applied to real-life situations?

Yes, this thought experiment can be applied to real-life situations, especially those involving risk and uncertainty. It can help individuals make more rational decisions by considering the potential outcomes and their probabilities.

5. Are there any criticisms of this thought experiment?

Some critics argue that this thought experiment oversimplifies decision-making and does not take into account other important factors, such as personal values and preferences. Others also point out that it assumes equal probabilities for each outcome, which may not always be the case in real-life scenarios.

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