2.1. Hypothesis
In the experiment the question then is asked if it is possible that the
from (
6) can be approximated (epsilon close) with (
5). It is easy trigonometry to acknowledge that
And so, combining (
5) with (
6) and (
7), the hypothesis can be reformulated as
The question then subsequently is whether or not hypothesis
from (
8) can be true at all. It requires a Kolmogorovian probability
to be equal to (epsilon close in experiment)
.
Because
is a continuous variable, we can only conclude that the event "observation of equal spin under angle
" is associated to a continuous random variable
X. It is a well known fact from probability theory that the probability of a point in a continuous random variable distribution of values, is zero [
8]. The probability in a continuous case is the area under the probability density
f curve. E.g.
Its principle complies with (
1). The event
"
number of equal spins registered for angle
x in a total of
N observations", is represented by a set of numerical values of a continuous random variable
X such that
. The probability of an interval for
X is e.g.
. Note that in Riemannian integration open endpoints are the limit of integration. There is, hence, no difference between
and
.
The above implies that in fact the hypothesis in (
8) contains
for
. As an illustration of [
8], we have
and
. This is for required
equal to
. We therefore find that
for
.
This in turn also implies that [
6], the probability density function
in (
9) is
for
. Note that
and
is what is required to see that
is true for arbitrary
.
However, this density function in (
10) is impossible for a Kolmogorov classical probability because
is not positive definite for
. Looking at the area under density curve, and the Additivity above. We then find, for
,
we have
and note,
. Under
we then find
. But
and so
, hence,
and this concurs with
and
The function
is not monotone on
. One cannot require that a classical Kolmogorov probability [
7] must produce in experiment, a series of data where negative probabilities are necessary in order to obtain
is true in (
8).
It is also interesting to note that the universe interval
has a probability
. When a
rule is required, it is found that
instead of the required unity. This requirement is also contrary to the Kolmogorov axioms determining classical probability [
7].
In addition, Alice and Bob are unaware of each other’s setting vectors. The whole range for x is therefore possible. Hence, for all we have . Moreover, quantum probability density does not exist and the quantum wave function is not a direct observable probability.
Let’s now turn to a possible discreteness or coarse graining. The claim that the angle is a discrete variable is also not leading to a genuine probability. Apart from the fact that for each possible
one is interested in Einstein extra variables, the following is true. Because
, it follows that sums of hypothetical discrete probabilities will possibly be
. I.e. there are discrete countable
possible such that
That is also obviously contrary to classical probability definitions; i.e. Certain event.
The conclusion is therefore that the angle most definitely reflects a continuous random variable with ditto statistics. Further, it turns out that this statistical approach is flawed. A probability below one single point in continuous density is zero [
8]. There are no negative probabilities in experiment. Bell’s starting point (
2) complies to classical Kolmogorov probability theory, viz. (
1). Modeling (
2) with an implicit negative probability requirement, is a defective statistical design of the experiment.