Probability Axioms: Explaining Their Definition

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Discussion Overview

The discussion revolves around the axioms of probability, specifically their definitions and implications. Participants explore the reasoning behind the standard axioms compared to simpler definitions of probability, as well as the application of these axioms in practical scenarios, such as with a biased coin.

Discussion Character

  • Exploratory
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • Some participants outline the standard axioms of probability and question why they are defined in that manner instead of using a simpler definition based on favorable outcomes.
  • Others argue that the simpler definition assumes all events are equally likely, which is not always the case, and that the axioms ensure probabilities align with intuitive understanding.
  • A participant expresses discomfort with the third axiom, suggesting it feels indirect, and proposes a more straightforward approach to calculating probabilities for a fair coin.
  • Another participant introduces a scenario involving a biased coin, prompting questions about the plausibility of the situation and how mathematics can inform decisions regarding bets on the coin's outcomes.
  • Responses indicate that some participants agree with the plausibility of the biased coin scenario and provide a probability for tails based on the axioms, while others reflect on the relevance of the axioms in their calculations.
  • A later reply acknowledges the importance of the third axiom in understanding the probability of outcomes for the biased coin example.

Areas of Agreement / Disagreement

Participants express differing views on the sufficiency of the axioms versus simpler definitions of probability. While some find the axioms necessary for a comprehensive understanding, others prefer more direct approaches. The discussion remains unresolved regarding the best way to define and calculate probabilities.

Contextual Notes

Some assumptions about the nature of events and their probabilities are not explicitly stated, and the discussion reflects varying interpretations of the axioms' implications in practical scenarios.

Avichal
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Axioms are: -
1) P(E) >= 0
2) P(S) = 1
3) P(E1 U E2 U ...) = P(E1) + P(E2) + ... if all are mutually exclusive

Why are the axioms defined in such a way? Why not this simple axiom: - Probability of an event is number of favorable outcomes divided by total number of outcomes?
 
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Avichal said:
Probability of an event is number of favorable outcomes divided by total number of outcomes?

That would assume that all events are equally likely, which - in general - they are not.
If S = { today it rains, today it doesn't rain } then P(today it rains) is not 1 / |S| = 1/2. If that were true, replace " it rains" by "we all die in a meteor impact".
So what you do is assign a probability P(s) to every ##s \in S##. The axioms make sure that it matches our intuition.
 
I am still not comfortable with the 3) axiom. It seems a bit indirect to me.
Suppose we toss a coin and we want to find the probabilities of heads and tails. Now P(H) + P(T) = 1 ... from 3)
Since both are equally probable both are equal and hence P(H) = P(T) = 1/2
It is all indirect. We could have directly said that out of two possibilities head or tail is one and thus it is 1/2
 
Suppose you have a coin which will be tossed (so [itex]S=\{\text{heads}, \text{tails}\}[/itex]), and it's weighted so that the probability of heads is 52%.

Q1) Does this seem like a plausible situation?
Q2) Does it seem plausible that mathematics can inform ones decisions of which bets to take concerning this coin?
Q3) What do you think is a reasonable answer to: "What's the probability of tails?"
 
economicsnerd said:
Q1) Does this seem like a plausible situation?
Yes.
economicsnerd said:
Q2) Does it seem plausible that mathematics can inform ones decisions of which bets to take concerning this coin?
Yes, although I am a bit unsure what you are asking.
economicsnerd said:
Q3) What do you think is a reasonable answer to: "What's the probability of tails?"
48%

Sorry but I couldn't find any relevance to my question earlier.
 
Avichal said:
Why not this simple axiom: - Probability of an event is number of favorable outcomes divided by total number of outcomes?

What would the probability of tails be for this rigged coin, using your definition above?
 
Avichal said:
economicsnerd said:
Q3) What do you think is a reasonable answer to: "What's the probability of tails?"
48%

Sorry but I couldn't find any relevance to my question earlier.
The relevance is that you used the third axiom to calculate that 48% figure.
 
D H said:
The relevance is that you used the third axiom to calculate that 48% figure.

Thinking more about it I realized the importance of the 3rd axiom. Nice example to make me understand.
Many Thanks!
 

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