Proving Equivalence of (1) and (2): On Measurability

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In summary, the conversation discusses proving the equivalence of two statements related to Lebesgue outer measure and open sets containing a subset of R. The first statement states that for any positive value e, there exists an open set containing E with a measure less than e. The second statement states that for any positive value e, there exists a finite union of open intervals with a measure less than e. The conversation includes attempts at proving one statement from the other and discusses using countably many disjoint open intervals to prove the second statement. The conversation ends with a request for tips on how to show that the infimum of a bounded sequence of positive integers is 0.
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Homework Statement

Let E be a subset of R and suppose the Lebesgue outer measure m*(E) is finite. Prove that the following two statements are equivalent:

(1) Given e > 0, there is an open set A containing E with m*(A\E) < e.
(2) Given e > 0, there is a finite union V of open intervals such that m*(V\E U E\V) < e.


Relevant equations
Here's a statement that may come in handy: For any subset X of R and any e > 0, there is an open set Y such that Y contains X and m*(Y) <= m*(X) + e.


The attempt at a solution
I haven't even bothered trying to prove that (2) implies (1) as I'm stuck on the proof that (1) implies (2). Here's what I have so far: Let e > 0. By (1), there is an A containing E with m*(A\E) < e/2. A is an open set, so it is the union of countably many open intervals. If "countably many" is finite, then we're done. Otherwise, start by picking an open interval from A that intersects E. Call it V. We have that m*(V\E) <= m*(A\E) < e/2. I need to prove that m*(E\V) < e/2. If I can't, then I can make V larger by adding to it another open interval from A that intersects E. I imagine that after doing this finitely many times, V will be large enough so that m*(E\V) < e/2. The problem is that I don't have any way of calculating m*(E/V). Any tips?
 
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I have figured out the following: A is the union of countably many disjoint open intervals, say I_1, I_2, ... Let V_i = E \ (I_1 U ... U I_i). We have that m*(V_1) is finite and that V_1 contains V_2 contains V_3 etc. Hence, m*(V_1) >= m*(V_2) >= ..., i.e. (m*(V_i)) is a bounded sequence of positive integers, so it converges to inf {m*(V_i)}. Now all I need to do is show that said inf is in fact 0. This, I have not been able to do. Any tips?
 

Related to Proving Equivalence of (1) and (2): On Measurability

1. What is the significance of proving equivalence between two measures?

Proving equivalence between two measures is important because it allows us to compare and interpret data accurately. It ensures that the measures are measuring the same thing and can be used interchangeably in analyses and experiments.

2. How is equivalence between two measures determined?

Equivalence between two measures is determined by conducting statistical tests and analyzing the results. These tests assess the level of agreement or correlation between the measures and determine if they are measuring the same underlying construct.

3. What are some common statistical tests used to prove equivalence?

Some common statistical tests used to prove equivalence include the t-test, ANOVA, correlation analysis, and regression analysis. These tests compare the means, variances, and correlations of the measures to determine if they are equivalent.

4. Can two measures be considered equivalent if they have slightly different results?

Yes, two measures can still be considered equivalent if they have slightly different results. The degree of difference allowed depends on the context and purpose of the study. It is important to consult with experts in the field to determine an acceptable level of difference.

5. Why is it important to establish equivalence before conducting an experiment?

Establishing equivalence before conducting an experiment is crucial because it ensures that the results of the experiment are valid and can be accurately interpreted. Without proving equivalence, it is difficult to determine if any differences observed in the data are due to the measures or the manipulation being studied.

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