Maya and the null hypothesis
Note before reading: I am not a statistician nor very talented in statistics. Please indicate if my thought experiment with comparing Maya and the null hypothesis appears faulty.
The concept (from Wiki):
“Maya, is the principal concept which manifests, perpetuates and governs the illusion and dream of duality in the phenomenal Universe. For some mystics this manifestation is real, but it is a fleeting reality; it is a mistake, although a natural one, to believe that Maya represents a fundamental reality or Truth.  Each person, each physical object, from the perspective of eternity is like a brief, disturbed drop of water from an unbounded ocean. The goal of enlightenment is to understand this — more precisely, to experience this: to see intuitively that the distinction between the self and the Universe is a false dichotomy. The distinction between consciousness and physical matter, between mind and body (refer bodymind), is the result of an unenlightened perspective.
“The word origin of maya is derived from the Sanskrit roots ma (“not”) and ya, generally translated as an indicative article meaning “that.” The mystic teachings in Vedanta are centered on a fundamental truth that cannot be reduced to a concept or word for the ordinary mind to manipulate. Rather, the human experience and mind are themselves a tiny fragment of this truth. In this tradition, no mind-object can be identified as absolute truth, such that one may say “That’s it.” So, to keep the mind from attaching to incomplete fragments of reality, a speaker could use this term to indicate that truth is “Not that.””
In some ways, Maya can function as the null hypothesis. Oddly, as you can see in the description below, one can not really ACCEPT a null hypothesis, however they can NOT REJECT it. Though food for thought… if one REJECTS the null hypothesis (Maya in this case), then it IMPLIES that one has accepted the stated hypothesis, BUT is the stated hypothesis a truth or clarity… or can every hypothesis act as a null hypothesis, thereby playing into Maya. So that we act to REJECT or NOT REJECT within Maya, perhaps thinking we have transcended Maya in that we assume our REJECTION of the null implies ACCEPTING of the stated.
Also from Wiki: “In statistical hypothesis testing, the null hypothesis (H0) formally describes some aspect of the statistical behaviour of a set of data; this description is treated as valid unless the actual behaviour of the data contradicts this assumption. Thus, the null hypothesis is contrasted against another hypothesis. Statistical hypothesis testing is used to make a decision about whether the data contradicts the null hypothesis: this is called significance testing. A null hypothesis is never proven by such methods, as the absence of evidence against the null hypothesis does not establish it. In other words, one may either reject, or not reject the null hypothesis; one cannot accept it. Failing to reject it gives no strong reason to change decisions predicated on its truth, but it also allows for the possibility of obtaining further data and then re-examining the same hypothesis.
For example, imagine flipping a coin three times, for three heads; and then forming the opinion that we have used a two-headed trick coin. Clearly this opinion is based on the premise that such a sequence is unlikely to have arisen using a normal coin. In fact, such sequences (three consecutive heads or three consecutive tails) occur a quarter of the time on average when using normal unbiased coins. Therefore the opinion that coin is two-headed has little support. Formally, the hypothesis to be tested in this example is “this is a two-headed coin”. One tests it by assessing whether the data contradicts the null hypothesis that “this is a normal, unbiased coin”. Since the observed data arises reasonably often by chance under the null hypothesis, we cannot reject the null hypothesis as an explanation for the data, and we conclude that we cannot assert our hypothesis on the basis of the observed sequence.”
If we view these as sets: rejecting set (R), not rejecting set (NR) and accepting set (A). By DEFINITION R and NR are completely separate, never overlapping or touching. However, A in relation to these 2 sets is usually seen as overlaying NR (i.e. binary mind frame defined by the 2 choices of R vs NR). If we are to look closer, A may appear to overlay NR, but there is just as likely an explanation for those 2 sets to never touch but appear to be joined/overlayed. Imagine a 3D view of the sets, with R and NR on the same plane. The way in which A will never touch NR is if A exists on an entirely different plane. By one viewpoint (bird’s eye) A and NR look the same, but by another (closer observation between planes) they are clearly completely different.