Probability of a probability of a. .

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The discussion centers on the concept of "probability of a probability," exploring its mathematical foundations based on Kolmogorov's axioms from the 1930s. Participants clarify that this concept aligns closely with conditional probabilities, illustrated through examples involving coin tosses and free throw statistics. The formula P(A|B) P(B) = P(B|A) P(A) is highlighted as a key relationship in understanding these probabilities. Additionally, the conversation touches on the distinction between conditional probabilities and expressions of confidence in statistical contexts.

PREREQUISITES
  • Understanding of Kolmogorov's axioms of probability
  • Familiarity with conditional probability concepts
  • Basic knowledge of statistical expressions of confidence
  • Awareness of Bayes' Theorem and its applications
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  • Study Kolmogorov's axioms of probability in detail
  • Learn about conditional probability and its applications
  • Explore Bayes' Theorem and its implications in statistics
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Mathematicians, statisticians, and anyone interested in advanced probability theory and its applications in real-world scenarios.

Loren Booda
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Does physics or mathematics allow for a probability of a probability?
 
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As a mathematical theory, modern probability is based on a set of axioms formulated by Kolmogoroff in the 1930's. To make a probability of probability theory, one can see if the axioms make sense in this case.
 
mathman,

For instance, if an event has a probability [mu] of probability [nu] of occurring, then can you say in general that the event has a probability [mu][nu] of occurring?
 
What you are talking about sounds a lot like conditional probabilities.

For events A and B, if:

P(A) = μ
P(B | A) = ν (that's probability that B occurs, given that A occurs)
P(A | B) = 1 (B can only occur if A occurs)

Then we can apply the formula

P(A|B) P(B) = P(B|A) P(A)
to get

P(B) = μ ν
 
Sure:

I throw a coin four times, the probailty that I get three heads is 0.25, but you can also say: The probability that the probailty after the second throw is 0.0625 is 0.5.
 
And has Hurkyl says, my example is a conditonal probability.
 
Thanks much for your explanations, folks. I will try to recondition my thinking accordingly.

Could you recommend a simple online source for conditional probability, Hurkyl? The notation slips me.
 
In the U.S. the typical example of a conditional probability is someone making the second free throw:

Jeff Hornachek (Don't remember spelling) had a 90% free throw rate, so on a double free throw, he had a 81% (or 90% of 90%) chance of making his second shot.

An alternative example would be from statistics or zero knowledge proofs where probability is used as an expression of confidence. Be wary that this type of double probability is something different than the conditional probalitity described above.

For example, there is a 90% probability that that loaded die has a 70% chance of rolling a 6.

Or from polling: There is a 95% probability (expressing confidence in the poll) that each voter has a 45% probability of voting for Arnie.
 
Sorry, I don't know of any resources in particular... I'd think about any introduction to probability would talk about it though.
 
  • #10
'sOK, NateTG gave some excellent examples. Practical interpretations of multiple probabilities tend to elicit different physical variables for each expectation, though. My first free throw might anticipate more rebound action than the second.

A Gaussian curve might be described as an infinite succession of probabilities, whereas a constant statistic could not. Endless deviatives of the Gaussian attest to the potential underlying infinite series of probabilities.
 
  • #11

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