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The
Mathematical Basis for the Inapplicability of Probability to Invalid
Functions
There are
frequent statements in the literature that facts can be assigned a
probability. These usually come in the form of asserting that the fact is
improbable (usually “highly improbable” or “surprising”). Some
writers making this claim should
know better.
Others
are best advised to stay away from mathematics altogether. The intuitive
(and mostly correct) response is that facts don’t have probabilities. They
just are. It is equally incorrect, however, to try to assign probabilities
to speculative possibilities. By speculative possibility I mean a
“probability function” every one of whose arguments (whose integrand if the
probability function can be integrated) is a function f(x) = x/∞. The most
rigorous way to show this is via the mathematics of probability. A random
variable or probability function is a rule or function that assigns a
numerical value to an outcome of an experiment. A probability distribution
is a list of all possible values of a random variable. The sum of
probabilities in a probability distribution or sample space must = 1. So the
probability of all possible valid outcomes is 1 and the probability of
excluded or invalid outcomes is 0. For example, the probability that a coin
toss will result in heads or tails is 1; the probability that the coin will
not land on the ground is 0. A valid probability is typically a rational
number, r, such that 0 ≤ r ≤ 1. The probability that a single coin toss will
result in heads is ½. A probability of 0 is impossibility and a probability
of 1 is inevitability or fact. Probability density functions or PDF’s of
continuous random variables are accumulation functions whose values are
probabilities (sums of the probabilities of continuous random variables over
a given interval). Constants are functions that assign a constant value to
every argument. If “n” stands for a constant, then the probability function
or random variable of n assigns the value 1 to n and the value 0 to
everything else. In this way a constant can be regarded as the outcome – the
only possible outcome – of an experiment. The probability distribution P(f(x)
= n) would contain only one member whose value is greater than 0. Facts (or
at least factual numerical measurements) are constants. I shall group the
probability functions of constants and speculative possibilities together
and call them “invalid probability functions.”
The graph of
the constant function f(x) = n is a horizontal straight line parallel to the
x-axis and intersecting the y-axis at n. E.g.:

The graph of
the PDF of a constant is a horizontal line parallel to the x-axis that
intersects the y-axis at 1. It satisfies the requirements for a PDF only at
intervals that are single points. It does so, however, for every single
point.
A speculative
possibility is a probability function P whose integrand is f(x) = x/∞. That
is, the random variable for any value of x yields x/∞. Thus it yields 0 for
every value of x (assuming x/∞ = 0; if x/∞ is undefined, then P(x/∞) is
invalid because it does not have a defined integrand). Its graph is a
horizontal line that coincides with the x-axis. It does not fulfill the
requirements of a PDF since there is no sample space S for f(x) such that
P(S) = 1. Since there is nothing to accumulate, the graph of a speculative
possibility would look the same as the graph of its random variable:

Assuming the
integrand of P = F(x) is f(x), then f(x) = F' (x) = 0. The speculative
possibility yields the same result as its random variable, viz. the constant
0 for any value of x in the random variable. It is not a valid probability
function since there is no interval at all whose value = 1. Speculative
possibilities, however, are not the same as the probability function
associated with the constant function f(x) = 0. The latter yields the
probability 1 for any value of x just like any other constant; the former
yields the probability 0 at x = 0 just as it does for any other value of x.
In terms of probability calculations the constant 0 should be looked upon as
the value of the integrand of a probability function whereas x/∞ in the case
we are considering is the value of a probability function (the probability
that some outcome x will obtain).
If you follow a
speculative possibility of possible universal constants construed as a
probability function to its logical conclusion, the universe doesn’t exist!
There is a point to grouping constant functions and speculative
possibilities as invalid functions for the purposes of discussing the
“probability” of a fact because those who try to assign a probability (or an
improbability) to a fact usually put themselves in a hypothetical situation
where, before the fact was actualized (for example, before the appearance of
the universe), alternatives appear to have been available. Of course this
imaginary scenario begs the question as to whether the facts were indeed
“chosen” among alternatives. Moreover, it cannot be evaluated using the
mathematics of probability because by hypothesis there are an infinite
number of possible outcomes for the value of the universal constant each
with exactly the same probability, namely x/∞. Since the value of every
possible argument of a speculative possibility is 0, it is impossible to
construct a sample space such that the sum of the probabilities of the
members of the sample space = 1. The mathematical impossibility, in my
opinion, undermines the validity of loose talk about improbabilities in
theological and cosmological speculation.
The error, I
believe, on the part of those who try to assign probability values to
speculative possibilities is that they misconstrue continuous probability
functions or PDF’s, those functions that assign a theoretically infinite
number of random variables to a theoretically infinite number of events. The
point is that a well-formed PDF still assigns a real n, such that 0 ≤ n ≤ 1
for every one of the potentially infinite number of random variables within
the sample space. And it still requires an interval for definite integration
(its sample space) whose accumulated probability value = 1. A speculative
possibility does not satisfy this requirement since it assigns 0 to every
random variable in its range.
Speculative
possibilities are also not the same as improper functions because, for one
thing, the sample space represented by a real number interval on the graph
of the speculative possibility need not equal or approach either ∞ or -∞. In
case it did so, a speculative possibility would remain invalid because it
would still assign the value 0 to every one of its arguments. Even an
infinitely long sample space on the graph of a speculative possibility could
not be constructed such that the sum of the probabilities of its arguments =
1.
There remains
the case where the observed or hypothetical constant is supposed to be a
real number interval with more than one member such as would be the case
where the actual constant could be any number within a margin of measurement
error. Obviously the fact that a measurement may have a margin of error does
not mean that the constant does not in fact have a single value. And there
is no evidence that the notion of a range of actual values for a universal
constant would make any sense in the context of physical theory. Moreover in
much of mathematics the expression “∞/∞” (which would express the
probability of a continuous number interval being an actual value out of a
continuous set of alternatives) is undefined. The proposals for defining
“∞/∞” do not help. For if ∞/∞ were to be defined as = 1, the result would be
that all number segments would be actual values of, say, a single universal
constant. Given any rational number, for example, that rational number would
be the correct (and observable?) value of the ratio between gravitation and
the strong nuclear force, an obvious absurdity. The proposal that “∞/∞” is
meaningful in case the numerator is greater than the denominator of the
expression depends on the assumption that the numerator of the expression
expresses an uncountable infinity and the denominator expresses a countable
infinity. I suspect that any meaningful discussion of the universal
constants would limit their values to the rational numbers in which case the
property of density of a given segment would not imply non-countable
infinity. But, even if the irrational numbers could be viable values for the
universal constants, there is no reason that the infinity of the denominator
may not include irrational numbers also and consequently be uncountable. It
would probably have to for, if irrationals are actual values of the
numerator, then irrationals would have to be possible values as well. In
fact for any ∞/∞ whose numerator denotes a set of all the real numbers
within the margin of error of a measurement and the denominator denotes a
set that is complementary to the numerator set, then the cardinality of both
the numerator and the denominator equals the cardinality of the continuum or .
Mill (probably
because of his reservations about the empirical applicability of the
mathematics of probability) knew this on a more informal level: “…in the
absence of any ground from experience for estimating (a thing’s – WD) degree
of probability, it would be idle to attempt to assign any.”
Logic p. 376
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