Proving Non-Negativity and Monotonicity of Integrals over a Measure Space

In summary, the conversation discusses the validity of the statement "if lf+-\phil<ε/(2\mu(E)) then ∫E lf+-\phil<ε/2" and concludes that it is correct based on the given equations and assumptions. The conversation also provides a hint for proving a related statement.
  • #1
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Homework Statement


My question is would I be allowed to say,
if lf+-[itex]\phi[/itex]l<ε/(2[itex]\mu[/itex](E)
then ∫E lf+-[itex]\phi[/itex]l<ε/2

Homework Equations



E is the set in which we are integrating over.
[itex]\mu[/itex] is the measure
[itex]\varphi[/itex] is a simple function
f+ is the non-negative part of the function f.

The Attempt at a Solution



I can't think of any reason that this wouldn't be true but my text is very vague in this chapter and so I am really not sure if this is an ok statement.



Thank you for your time.
 
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  • #2
Yes, your conclusion is correct.

It's not hard to prove the following:
##\newcommand{dmu}{\operatorname{d}\!\mu}##

(a) If ##f\geq 0## a.e., then ##\int f\dmu \geq 0##.
(b) If ##f\geq g\geq 0## on E, then ##\int_E f\dmu\geq\int_E g\dmu##.

Hint: To prove (b), use (a) and the fact that the assumption implies that ##f\chi_E\geq g\chi_E## (everywhere, and therefore a.e.).
 

1. What is the definition of measure theory?

Measure theory is a branch of mathematics that deals with the concepts of size, area, and volume of sets and their corresponding functions. It provides a rigorous framework for understanding and manipulating these basic concepts in a more general setting, allowing for the development of more advanced mathematical theories.

2. What are the basic concepts in measure theory?

The basic concepts in measure theory include sets, measures, and measurable functions. Sets are collections of objects, measures assign a numerical value to these sets, and measurable functions are functions that preserve the size of sets in some way.

3. What is the importance of measure theory?

Measure theory is important because it provides a rigorous and systematic approach to measuring the size of sets and their corresponding functions. It is used in many areas of mathematics, such as probability theory, analysis, and topology, and has applications in fields such as physics, economics, and computer science.

4. What are some examples of measures?

Examples of measures include length, area, volume, and probability. In measure theory, measures are often defined in terms of integrals, such as the Lebesgue measure, which assigns a length to a set in the real line and is used in the development of the Lebesgue integral.

5. What is the difference between discrete and continuous measures?

Discrete measures are defined on countable sets, while continuous measures are defined on uncountable sets. In other words, discrete measures can only take on a finite or countably infinite number of values, while continuous measures can take on an uncountable number of values. This distinction is important in the development of measure theory and the types of sets and functions that can be measured.

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