Measuring Disjoint Sets with Lebesgue Outer Measure

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In summary, the conversation discusses proving two statements related to the Lebesgue outer measure of subsets of R. The first statement involves proving that if the distance between two subsets is greater than 0, then the outer measure of their union is equal to the sum of their individual outer measures. The second statement involves proving the same result, but without using any facts about measurability. Possible approaches for the second statement include using the definition of outer measure and the compactness of the subsets.
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Homework Statement


Let X, Y be subsets of R and defined d(X, Y) = inf {|x - y| : x in X and y in Y}.

(i) Prove that if d(X, Y) > 0, then m*(X cup Y) = m*(X) + m*(Y)

(ii) Prove, without using any facts about measurability, that if X, Y are disjoint and compact, then m*(X cup Y) = m*(X) + m*(Y).


Homework Equations


m* is Lebesgue outer measure.


The Attempt at a Solution


Concerning (i), d(X, Y) > 0 implies that X and Y are disjoint right? But being disjoint is not enough to conclude that m*(X cup Y) = m*(X) + m*(Y).

Concerning (ii), since X and Y are disjoint, d(X, Y) > 0 and so part (i) applies and we're done. Since we're not supposed to use measurability, I imagine that (i) uses measurability so this isn't allowed. I guess I'm forced to work with the definition of outer measure. By monotonicity of m*, m*(X cup Y) ≤ m*(X) + m*(Y) so I only need to prove the reverse inequality. Let {U_n} and {V_n} be coverings of X and Y by open intervals. Then {W_n} = {U_n} cup {V_n} is an covering of X cup Y. By compactness, we can shrink each of {U_n}, {V_n} and {W_n} so that they are finite. Now {W_n} subseteq {U_n} cup {V_n}, so that sum L(W_n) ≤ sum L(U_n) + sum L(V_n), where L() returns the length of the interval. This is all I can think of. Any tips?
 
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  • #2
for (i) let d = d(X,Y), and [tex]O = \bigcup_{x\in X}(x - d,x+d)[/tex] so [tex]O\bigcap Y = empty set, [/tex] and [tex] X \subseteq O[/tex] then since O is measurable we get:

[tex]m(X\cup Y) = m((X\cup Y)\cap O) + m((X\cup Y)\cap O^{c}) = m(X) + m(Y). [/tex]
 
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  • #3
I thought of that exact same argument. Thanks. Any ideas on (ii)?
 

1. Can you explain the concept of measurability?

Measurability refers to the ability to quantify or measure a particular quantity or attribute using a standardized unit or scale. In science, this is essential for accurately collecting and analyzing data.

2. How is distance measured in science?

In science, distance is typically measured using standard units such as meters, centimeters, or kilometers. These units can be converted into other units depending on the scale of the measurement.

3. What is the importance of accurate measurements in science?

Accurate measurements are crucial in science because they provide objective and reliable data that can be used for analysis and experimentation. Without accurate measurements, it would be difficult to draw meaningful conclusions from scientific studies.

4. How do scientists ensure the accuracy of their measurements?

Scientists use various techniques and tools, such as instruments and calibration methods, to ensure the accuracy of their measurements. They also follow standardized protocols and repeat experiments to minimize errors.

5. Can distance be measured accurately without using tools?

It is difficult to measure distance accurately without using tools, as human perception can be subjective and prone to error. However, with careful observation and estimation, scientists can make relatively accurate measurements of distance without tools.

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