Understanding probability, is probability defined?

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Discussion Overview

The discussion revolves around the definition and conceptual understanding of probability, particularly in relation to its foundational theories and models. Participants explore the implications of defining probability in terms of relative frequency versus its axiomatic treatment as a measure. The conversation touches on theoretical constructs, practical applications, and the philosophical aspects of probability.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant expresses confusion about the lack of a clear definition of probability in statistics books, noting that probability is often described in terms of events and relative frequency without being explicitly defined.
  • Another participant argues that theorems in probability only discuss the likelihood of relative frequency approaching certain values, suggesting that this does not guarantee specific outcomes.
  • It is noted that the axiomatic development of probability treats it as a "measure" rather than defining it through relative frequency, with no assumptions about actual events occurring.
  • Some participants highlight that the formalism of probability includes states of the world, events, and a numerical measure assigned to events, which exists independently of interpretation.
  • A participant questions whether the core definition of probability as a measure of likelihood is sufficient for practical applications like calculating expected values and confidence intervals.
  • Concerns are raised about the logical progression in learning probability, particularly how foundational concepts like expected value relate to the relative frequency model, which seems to be introduced later in the learning process.
  • Clarification is made that probability is defined as a "measure" in a mathematical sense, distinct from being a "measure of likelihood," which may lead to misunderstandings.

Areas of Agreement / Disagreement

Participants express a mix of agreement and disagreement regarding the definition and interpretation of probability. While some agree on the axiomatic approach, others challenge the implications of defining probability in terms of relative frequency, leading to an unresolved debate on the foundational understanding of the concept.

Contextual Notes

Participants note limitations in the definitions and assumptions surrounding probability, particularly concerning the relationship between theoretical constructs and practical applications. The discussion reveals a gap in understanding how foundational concepts are interrelated and the implications of different interpretations of probability.

  • #61
bobby2k said:
Or is it inevitable that we would use "belief" in explaining/justifying that we approximate a probability with a finite relative frequency?

If you have a mathematical theory that deals with one set of concepts ( e.g. weight, mass, position) and you try to apply it to a situation defined by a different set of concepts (e.g. price, value, utility) then you must introduce assumptions that establish some relation between the different concepts. You can introduce assumptions as formal mathematical axioms (which is necessary if you intend to prove your results) or you can introduce assumptions by your personal beliefs in an informal manner.

As far as I know, nobody has created a set of axioms for probability theory that establishes any deterministic relation between the relative frequency of an event and its probability. So if you want to establish such a relationship, you must do it using your personal beliefs - or else invent the mathematics that does the job.
 
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  • #62
There is nothing mystical about probabilities. Given a set of data, it is obvious, and dirt simple, to ask which fraction or percentage satisfies certain conditions. Scaling those numbers to a [0,1] scale or to a [0%, 100%] scale is just computationally convenient. Also, using the past events (statistics of past experiences) to anticipate similar future events (probabilities of future outcomes) is critical to the survival of even the simplest thinking animals.
 
  • #63
Stephen Tashi said:
If you have a mathematical theory that deals with one set of concepts ( e.g. weight, mass, position) and you try to apply it to a situation defined by a different set of concepts (e.g. price, value, utility) then you must introduce assumptions that establish some relation between the different concepts. You can introduce assumptions as formal mathematical axioms (which is necessary if you intend to prove your results) or you can introduce assumptions by your personal beliefs in an informal manner.

As far as I know, nobody has created a set of axioms for probability theory that establishes any deterministic relation between the relative frequency of an event and its probability. So if you want to establish such a relationship, you must do it using your personal beliefs - or else invent the mathematics that does the job.

Thank you, I now have the understanding I wanted about this subject. Sorry for taking so much time to understand it, but thank you very much for beeing patient!
 
  • #64
"On voit, par cet Essai, que la théorie des probabilités n'est, au fond, que le bon sens réduit au calcul; elle fait apprécier avec exactitude ce que les esprits justes sentent par une sorte d'instinct, sans qu'ils puissent souvent s'en rendre compte."

"One sees, from this Essay, that the theory of probabilities is basically just common sense reduced to calculus; it makes one appreciate with exactness that which accurate minds feel with a sort of instinct, often without being able to account for it."

Pierre-Simon Laplace, from the Introduction to Théorie Analytique des Probabilités.
 

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