Re: Does a "pure" real valued probability make any sen

From: Sam Wormley (swormley1_at_mchsi.com)
Date: 12/03/04 

Date: Fri, 03 Dec 2004 00:14:40 GMT

SkanderH wrote:
> According to most text books the definition of the probabilty of an
> outcome is that if you could (ideally) perform an experiment to test
> this outcome a (infinite) large number of times then the probability
> of the outcome is the ratio of the number of successful outcomes to
> the total number of experiments.

Ref: http://mathworld.wolfram.com/Probability.html

   Probability is the branch of mathematics that studies the
   possible outcomes of given events together with the outcomes'
   relative likelihoods and distributions. In common usage, the
   word "probability" is used to mean the chance that a particular
   event (or set of events) will occur expressed on a linear scale
   from 0 (impossibility) to 1 (certainty), also expressed as a
   percentage between 0 and 100%. The analysis of events governed
   by probability is called statistics.

   There are several competing interpretations of the actual
   "meaning" of probabilities. Frequentists view probability simply
   as a measure of the frequency of outcomes (the more conventional
   interpretation), while Bayesians treat probability more
   subjectively as a statistical procedure that endeavors to
   estimate parameters of an underlying distribution based on the
   observed distribution.

   A properly normalized function that assigns a probability
   "density" to each possible outcome within some interval is
   called a probability function (or probability distribution
   function), and its cumulative value (integral for a continuous
   distribution or sum for a discrete distribution) is called a
   distribution function (or cumulative distribution function).

See: http://mathworld.wolfram.com/Probability.html

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