Limit definition and infinitely often

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SUMMARY

The discussion centers on the definition of limits in the context of sequences of real numbers and the interpretation of probability notation. It establishes that for a sequence \( x_n \) converging to \( x \), the condition \( P(|x_n - x| < \epsilon \text{ i.o.}) = 1 \) is valid under the assumption that \( x_n \) consists of real numbers. However, it clarifies that the notation \( P(\cdot) \) implies a probability, which necessitates the presence of a random variable and its distribution. The conversation emphasizes the distinction between sequences of real numbers and sequences of random variables in limit definitions.

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Limit definition and "infinitely often"

If we have a sequence of real numbers x_{n} converging to x, that means \forall \epsilon &gt; 0, \exists N such that |x_n - x| &lt; \epsilon, \forall n \geq N.

So, can we say P (|x_n - x| &lt; \epsilon \ i.o.) = 1 because for n \geq N, |x_n - x| &lt; \epsilon always holds?
 
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adnaps1 said:
So, can we say P (|x_n - x| &lt; \epsilon \ i.o.) = 1

Is that notation suppose to denote a probability? It doesn't define a probability until you establish a scenario that specifies at least one random variable and its probability distribution. Are you thinking of "picking an x_i at random"? Or did you mean the x_i to be a sequence of real valued random variables instead of a sequence of real numbers? (If the x_i are random variables, you have to use a different definition of limit than the one you gave.)
 


Yes, the notation P(\cdot) was supposed to denote a probability, and I want the x_i to be a sequence of real numbers, not random variables. But I understand what you're saying. I cannot talk about probabilities without having a random variable.
 

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