Limits of Sequences .... Stoll Theorem 2.2.6

In summary: In going from: \frac{1}{ n^p } \lt \epsilon ton \gt \frac{1}{ \epsilon^{ \frac{1}{ p } }}What are the axioms or theorems or definitions of the real Nos that you use??
  • #1
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In his book: Introduction to Real Analysis, Manfred Stoll does not prove parts (a) and (b) of Theorem 2.2.6 on the limits to certain special sequences ...

I am having trouble getting started on the proof of part (a) ... can someone please help me to make a meaningful start to the proof ... (despite the fact that Stoll informs us that the proof is straightforward ... :( ... )

Theorem 2.2.6 reads as follows:

View attachment 7194Peter
 
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  • #2
Peter said:
In his book: Introduction to Real Analysis, Manfred Stoll does not prove parts (a) and (b) of Theorem 2.2.6 on the limits to certain special sequences ...

I am having trouble getting started on the proof of part (a) ... can someone please help me to make a meaningful start to the proof ... (despite the fact that Stoll informs us that the proof is straightforward ... :( ... )

Theorem 2.2.6 reads as follows:

Peter

After some reflection I have a proposed solution ...To show \(\displaystyle \text{lim}_{ n \rightarrow \infty } = 0\) Now ... for any \(\displaystyle \epsilon \gt 0\) the inequality \(\displaystyle \left\lvert\frac{1}{ n^p } - 0\right\rvert \lt \epsilon\)gives \(\displaystyle \frac{1}{ n^p } \lt \epsilon\) or \(\displaystyle n \gt \frac{1}{ \epsilon^{ \frac{1}{ p } }}\) ... ... Hence ... if we take \(\displaystyle N \gt \frac{1}{ \epsilon^{ \frac{1}{ p } } } \) ... then for \(\displaystyle n \gt N\) we have ...\(\displaystyle \frac{1}{ n^p } \lt \left(\frac{1}{ \frac{1}{ \epsilon^{ \frac{1}{p} } } }\right)^p = \epsilon \)Is that correct?

Peter
 
Last edited:
  • #3
Peter said:
After some reflection I have a proposed solution ...To show \(\displaystyle \text{lim}_{ n \rightarrow \infty } = 0\) Now ... for any \(\displaystyle \epsilon \gt 0\) the inequality \(\displaystyle \left\lvert\frac{1}{ n^p } - 0\right\rvert \lt \epsilon\)gives \(\displaystyle \frac{1}{ n^p } \lt \epsilon\) or \(\displaystyle n \gt \frac{1}{ \epsilon^{ \frac{1}{ p } }}\) ... ... Hence ... if we take \(\displaystyle N \gt \frac{1}{ \epsilon^{ \frac{1}{ p } } } \) ... then for \(\displaystyle n \gt N\) we have ...\(\displaystyle \frac{1}{ n^p } \lt \left(\frac{1}{ \frac{1}{ \epsilon^{ \frac{1}{p} } } }\right)^p = \epsilon \)Is that correct?

Peter
Yes! (Yes)
 
  • #4
Opalg said:
Yes! (Yes)
Thanks Opalg ... it gives me great confidence when you or Evgeny confirm my effort ...

Thank you ...

Peter
 
  • #5
Peter said:
After some reflection I have a proposed solution ...To show \(\displaystyle \text{lim}_{ n \rightarrow \infty } = 0\) Now ... for any \(\displaystyle \epsilon \gt 0\) the inequality \(\displaystyle \left\lvert\frac{1}{ n^p } - 0\right\rvert \lt \epsilon\)gives \(\displaystyle \frac{1}{ n^p } \lt \epsilon\) or \(\displaystyle n \gt \frac{1}{ \epsilon^{ \frac{1}{ p } }}\) ... ... Hence ... if we take \(\displaystyle N \gt \frac{1}{ \epsilon^{ \frac{1}{ p } } } \) ... then for \(\displaystyle n \gt N\) we have ...\(\displaystyle \frac{1}{ n^p } \lt \left(\frac{1}{ \frac{1}{ \epsilon^{ \frac{1}{p} } } }\right)^p = \epsilon \)Is that correct?

Peter

In going from: \(\displaystyle \frac{1}{ n^p } \lt \epsilon\) to

\(\displaystyle n \gt \frac{1}{ \epsilon^{ \frac{1}{ p } }}\)

What are the axioms or theorems or definitions of the real Nos that you use??
 

Related to Limits of Sequences .... Stoll Theorem 2.2.6

1. What are the "limits of sequences"?

The "limits of sequences" refer to the behavior of a sequence as the terms in the sequence approach a certain value. In other words, it is the value that a sequence is approaching or converging to.

2. What is Stoll Theorem 2.2.6?

Stoll Theorem 2.2.6 is a mathematical theorem that states that if a sequence is bounded and monotonic, then it is convergent. This means that if a sequence is always increasing or always decreasing and its terms do not exceed a certain value, then it will converge to a specific value.

3. How is Stoll Theorem 2.2.6 used in mathematics?

Stoll Theorem 2.2.6 is used in mathematics to prove the convergence of a sequence. It is a useful tool for determining the behavior of a sequence and whether it will eventually converge to a specific value or not.

4. What are some examples of sequences that follow Stoll Theorem 2.2.6?

Some examples of sequences that follow Stoll Theorem 2.2.6 include the Fibonacci sequence, where each term is the sum of the previous two terms, and the geometric sequence, where each term is multiplied by a constant factor.

5. Are there any limitations to Stoll Theorem 2.2.6?

Yes, there are limitations to Stoll Theorem 2.2.6. It only applies to bounded and monotonic sequences, so it cannot be used for all types of sequences. Additionally, it does not guarantee that a sequence will converge, just that it is possible for it to converge.

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