Can there be ratios using different sizes of infinities?

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In summary, the conversation revolves around the concept of choosing a random number from an infinite set of numbers and the difficulties in calculating the probability of selecting a specific number from this set. The discussion also touches on the idea of using a continuous distribution versus a discrete distribution and the implications of both. Ultimately, the conversation highlights the challenges in assigning probabilities to events involving infinite sets.
  • #1
student34
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Pretend that some god has every real number in its head, and it is thinking of only one of them randomly. There seems to be a better chance of it being a real number, minus the naturals, rather than just a natural number. If this example is even allowed to be conceived, what does the ratio look like? If it is ℵ0/C, and the quotient is ≤ ℵ0, wouldn't it mean that there is a 0% chance of picking a rational number?

Also, if this logic is not ridiculous, then pretend that this time the god thought of a rational number instead. Isn't there a greater chance of it being a integer rather than just a natural number? If so, then how can the naturals and the integers have the same cardinality?
 
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  • #2
student34 said:
Pretend that some god has every real number in its head, and it is thinking of only one of them randomly.

This question is meaningless unless you specify how the numbers are being chosen.
If we had a six sided die, I can say "with equal probability choose a number". Each element has probability 1/6. There are six sides, each 1/6, so they add to 1 (i.e. 100%)

I can't do this with an infinite set. If the probabilities are equal, then adding an infinite number will give me infinity, not 1.

If I want to choose (say) "a natural number at random" I need them to be different probabilities. Eg. The probability of choosing n could be 2-n.
 
  • #3
Hey student34 and welcome to the forums.

There are a few issues here.

First of all if you are allowed to choose a specific number it means that you can not model this with a continuous distribution, since a continuous distribution allows you to only consider the probability of a non-zero interval (and unions thereof).

So this means you have a discrete distribution for a start.

So in the way you have stated your question, you can't even construct a proper distribution in the above manner, if you are trying to use a continuous distribution. You also need to specify a proper probability for each outcome that is non-zero. If every outcome has the same probability and the number of events tends to infinity, then you get a probability of zero and this reflects one way of interpreting why the probability of a single point in a continuous distribution is zero: they both correspond to the same situation happening.

If you do however want to consider the experiment, you either need to create a continuous distribution where a non-zero interval corresponds to some event (like the naturals, integers, rationals whatever) and the complement corresponds to everything else: if this is properly defined in all aspects (i.e. Kolmogorov Axioms, definition of PDF makes sense in context of the problem) then you can use that to calculate your PDF.
 
  • #4
Sorry, but I just don't know enough about math to know why my OP doesn't make sense. I probably should have even asked.
 
  • #5
student34 said:
Sorry, but I just don't know enough about math to know why my OP doesn't make sense. I probably should have even asked.

Basically it boils down to you specifying a distribution so that you can calculate a probability.

The post I mentioned above says the reason why you can't use a continuous distribution and the reason is that you can't just calculate a probability for one value in a continuous distribution because it is zero. You can calculate a probability for a collection of values like say from 0 to 0.1 or 1 to 1.0000011 or something like that but not for an interval that is essentially 0 length. So it means we need a discrete distribution.

Now you have an infinite number of values and if it really is random its going to be uniform (basically the probability of picking any value is the same as all the other values) which means if you have N choices, then the probability is 1/N. But you have infinitely many numbers and the limit of the probability in this case is 0.

This is the paradox: if you use the above formulation you don't even get a proper probability to begin with and you automatically have problems.

The only way to really settle this is to check that the ratio of cardinalities is non-zero if you wish to say "bunch up all natural numbers" as one event and everything else as the complementary event instead of the way I did above which was to treat every single possible numeric outcome as a single event. Doing what I did shows that the probability is zero and doesn't even make sense, but if you can show that you can obtain a non-zero probability for the ratio of cardinalities, then this means that you can obtain a probability.
 
  • #6
In application (if this is even possible), it would be so close to 0, they would consider it 0%, but the real issue is, this is a limit & infinite series problem as chiro says. The chances of picking any specific number would approach 0. Check out / review the Infinite Series (with rieman sums). It might help you come to your own conclusion ;D
 
  • #7
What the OP is asking, although extended to all the integers, may be modeled by a Dirac comb function. However, this distribution is non-normalizible.
 

1. Can infinities of different sizes be compared?

Yes, infinities can be compared using the concept of cardinality. Two sets have the same cardinality if there exists a one-to-one correspondence between the elements of the sets. This means that for every element in one set, there is a corresponding element in the other set. If this is true, then the two sets are said to have the same size or cardinality.

2. How do we determine the size of an infinity?

The size of an infinity is determined by its cardinality. A set with a higher cardinality has a larger size. For example, the set of natural numbers (1, 2, 3...) has a smaller cardinality than the set of real numbers, meaning that the set of real numbers is larger in size.

3. Can there be an infinity larger than another infinity?

Yes, there are different sizes of infinities and some infinities are larger than others. This is known as the Cantor's diagonal argument, which states that for any set, the power set (set of all its subsets) has a larger cardinality. Therefore, the power set of the set of natural numbers is larger than the set of natural numbers itself.

4. Are there any practical applications for understanding different sizes of infinities?

Yes, understanding different sizes of infinities is important in fields such as mathematics and computer science. In mathematics, it allows for a deeper understanding of the concept of infinity and its applications, such as in calculus and set theory. In computer science, it is used in algorithms, data structures, and computational complexity theory.

5. Is infinity a number?

No, infinity is not a number. It is a concept that represents something without an end or limit. It cannot be used in calculations in the same way as regular numbers, and it does not follow the same rules of arithmetic. Infinity is often used in mathematics to represent unbounded quantities, but it is not a number in the traditional sense.

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