Single event probability equivalent to that of its permutations?

Click For Summary
The discussion centers on whether the probability of a specific event in a set is equivalent to the total probability of all permutations involving that event. Participants clarify that the initial question lacks coherence, as permutations do not directly relate to the probability of individual events. It is noted that the total number of permutations is greater when including a specific event compared to when it is excluded. The conversation highlights a misunderstanding of how permutations and probabilities interact. Ultimately, the original inquiry is deemed redundant and not meaningful in the context of probability theory.
Loren Booda
Messages
3,108
Reaction score
4
Is the probability for a particular event, out of a set of events, equal to the total [normalized?] probability for all permutations of events from the set, including the particular event?

Say you have a 2 x 2 square with cells numbered 1 to 4. I am asking if the probability for square 1, p(1) is equal to the total probability for its permutations, p(1,2)+p(1,3)+p(1,4)+p(1,2,3)+p(1,2,4)+p(1,3,4)+p(1,2,3,4). Or should I divide this by the number of permutations?
 
Last edited:
Physics news on Phys.org
Loren Booda said:
Is the probability for a particular event, out of a set of events, equal to the total [normalized?] probability for all permutations of events from the set, including the particular event?

The answer is almost surely no, whatever question you meant to ask. Just suppose that something has zero probability.

Say you have a 2 x 2 square with cells numbered 1 to 4. I am asking if the probability for square 1,

This doesn't make sense. I have a square with 4 numbers. This is nothing to do with probabilities.

p(1) is equal to the total probability for its permutations, p(1,2)+p(1,3)+p(1,4)+p(1,2,3)+p(1,2,4)+p(1,3,4)+p(1,2,3,4). Or should I divide this by the number of permutations?


How is P(1,2) a permution of P(1)?
 
Consider this, demonstrable no doubt by the binomial theorem:

Given a set of events occurring with equal probability, the total number of permutations including a given event is one more than the total number of permutations without that event.
 
I'll say it again: the total number of permutations of what?

There are 6 permutations of the numbers 1,2,3 and 4 permutations of 1,2. You know, n!, right? And again, probability has nothing to do with this fact.
 
matt,

It turns out, upon further inspection, that what I was trying to describe is a redundancy. Sorry for the wild goose chase.
 
The standard _A " operator" maps a Null Hypothesis Ho into a decision set { Do not reject:=1 and reject :=0}. In this sense ( HA)_A , makes no sense. Since H0, HA aren't exhaustive, can we find an alternative operator, _A' , so that ( H_A)_A' makes sense? Isn't Pearson Neyman related to this? Hope I'm making sense. Edit: I was motivated by a superficial similarity of the idea with double transposition of matrices M, with ## (M^{T})^{T}=M##, and just wanted to see if it made sense to talk...

Similar threads

  • · Replies 16 ·
Replies
16
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 6 ·
Replies
6
Views
3K
  • · Replies 36 ·
2
Replies
36
Views
4K
Replies
10
Views
1K
  • · Replies 8 ·
Replies
8
Views
1K
  • · Replies 29 ·
Replies
29
Views
4K
Replies
147
Views
10K
  • · Replies 2 ·
Replies
2
Views
2K