Simple (I think?) measure theory question

In summary, to find the measure of a set difference, m(A-B), you can use the formula m(A-B) = m(A) - m(A\cap B) or the formula m(A-B) + m(A\cap B) = m(A), which holds even if m(A) = \infty. This can also be justified by looking at a Venn diagram and thinking of areas as the measure. Additionally, for any sets S and T, we have S-T = S - (S\cap T), which can be seen both informally through a Venn diagram and formally through the additivity property of measures.
  • #1
AxiomOfChoice
533
1
If you have two measurable sets [itex]A[/itex] and [itex]B[/itex] (not necessarily disjoint), is there an easy formula for the measure of the difference, [itex]m(A-B)[/itex]?
 
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  • #2
[tex]m(A-B) = m(A) - m(A\cap B)[/tex]
or, slightly better since it holds even if [tex]m(A) = \infty[/tex],
[tex]m(A-B) + m(A\cap B) = m(A)[/tex]
 
  • #3
By set difference do you mean symmetric difference?
[tex] A-B= A\cap \overline{B} \cup \overline{A}\cap B[/tex]
where overline is set complement?

g_edgar's formulas are for:
[tex] A-B = A \cap \overline{B}= \{ x | x\in A \, \&\, x\not\in B\}[/tex]

I'll use ~ for symmetric difference and then:
[tex] m(A \sim B) = m(A) + m(B) - m(A\cap B)[/tex]
Its just a matter of looking at a Venn diagram and thinking of areas as the measure.
 
  • #4
g_edgar said:
[tex]m(A-B) = m(A) - m(A\cap B)[/tex]
or, slightly better since it holds even if [tex]m(A) = \infty[/tex],
[tex]m(A-B) + m(A\cap B) = m(A)[/tex]
Thanks! But can you explain why this is this justified? There is a corollary in my textbook that gives [itex]m(B-A) = m(B) - m(A)[/itex] if [itex]A\subseteq B[/itex]. Do we have [itex]S-T = S - (S\cap T)[/itex] for any sets [itex]S[/itex] and [itex]T[/itex]? If we do, I'm satisfied...
 
  • #5
AxiomOfChoice said:
Do we have [itex]S-T = S - (S\cap T)[/itex] for any sets [itex]S[/itex] and [itex]T[/itex]? If we do, I'm satisfied...

Of course you do! S-T is the points in S that are not in T. But the only points that can be removed from S are the points in T that are also in S. And [itex]S-(S \cap T)[/itex] is precisely the points in S except for the points in T also in S. It's nearly a semantic proof
 
  • #6
Informally you see it in a Venn diagram.
Formally you look at the additivity property of measures, i.e. the measure of the union of disjoint sets is the sum of the measures of the pieces.

When dealing with any combination of unions and/or intersections simply break the set in question down into its smallest** pieces.

Example: Given initial sets A, B, and C you can break A up into A = ABC U ABC' U AB'C U AB'C' (where I'm using AB for A intersect B and B' for complement of B.)

**(smallest in terms of not further divisible by intersection with a given set or set's complement.)

This is very very straightforward stuff. Again draw a Venn diagram! I think you may be over thinking this.
 

FAQ: Simple (I think?) measure theory question

1. What is measure theory?

Measure theory is a branch of mathematics that deals with measuring the size or extent of sets. It provides a rigorous framework for defining and analyzing concepts such as length, area, and volume.

2. Why is measure theory important?

Measure theory is important because it allows us to define and study concepts such as size and volume in a precise and consistent manner. It has applications in various fields such as probability, statistics, and analysis.

3. What is a measure?

A measure is a mathematical function that assigns a numerical value to sets, representing their size or extent. It satisfies certain properties, such as non-negativity, countable additivity, and monotonicity.

4. What is the difference between a measure and a metric?

While both measure and metric are ways to quantify sets, they differ in their definitions and properties. A measure assigns a numerical value to sets, whereas a metric measures the distance between points in a set. Additionally, measures are defined for sets, while metrics are defined for points in a set.

5. What is Lebesgue measure?

Lebesgue measure is a type of measure that is used to measure the size of subsets of Euclidean space. It is named after French mathematician Henri Lebesgue and is based on the concept of length, which is defined as the smallest interval containing a given set.

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