What is the Difference Between Almost Upper Bounds and Upper Bounds in Calculus?

In summary, the author defines an "almost upper bound" as a number x that has only finitely many numbers y in a set A that are greater than or equal to x. The reader is asked to prove that if A is a bounded infinite set, then the set of all almost upper bounds for A is non-empty and bounded below. However, a concrete example leads to confusion as it seems that any number larger than or equal to 1 would be an almost upper bound. The definition does not require x to be a member of A and for finite sets, all numbers are almost upper bounds.
  • #1
jgens
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The author of my calculus book defines an "almost upper bound" as follows: A number [itex]x[/itex] is an almost upper bound for the set [itex]A[/itex] if there are only finitely many number [itex]y \in A[/itex] with [itex]y \geq x[/itex].

He then asks the reader to prove that if [itex]A[/itex] is a bounded infinite set, then the set [itex]B[/itex] of all almost upper bounds for [itex]A[/itex] is non-empty and bounded below. This seemed simple enough but I got confused when I thought about it in terms of a concrete example. Here are my thoughts . . .

Let [itex]A = (0,1)[/itex] and [itex]x[/itex] be an almost upper bound for [itex]A[/itex]. Clearly [itex]x[/itex] can be written in the form [itex]x = 1 - \varepsilon[/itex] where [itex]0 < \varepsilon < 1[/itex]. Since [itex]x[/itex] is an almost upper bound, there should only be finitely many numbers [itex]y \in A[/itex] with [itex]y \geq x[/itex]. However, since the infinite sequence of numbers [itex]1-\varepsilon/2, 1-\varepsilon/3, 1-\varepsilon/4, . . . [/itex] are all in [itex]A[/itex] and greater than [itex]x[/itex] this is a contradiction.

Could someone help me figure out where I went wrong in my thinking? Thanks.
 
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  • #2
I was very confused.when i first came acrosse this.best tthing to do is try and remeber and "swat for yur exmas" it worked for me
 
  • #3
Why must x be in A? Wouldn't 1 be an almost upper bound of that set, since there are 0 elements in A greater than or equal to 1?
 
  • #5
Tiny-tim: This is from Spivak's Calculus

Thanks for the explanation guys! I guess I just wasn't thinking about this the right way.
 
  • #6
For an interval like that, an "almost upper bound" is exactly the same as an upper bound.

If the set were, say [itex](0, 1)\cup \{2\}[/itex] any number larger than or equal to 2 would be an upper bound but any number larger than or equal to 1 would be an "almost upper bound". Both sets are non-empty and bounded below.

For a finite set finite set all numbers are "almost upper bounds"- which is why that theorem specifies that the set must be infinite.
 

What is upper bound confusion?

Upper bound confusion is a concept in computer science and mathematics that refers to a situation where there is uncertainty about the maximum possible value for a given variable or parameter. It can also arise when there is confusion about which upper bound is being referred to in a particular problem or equation.

How does upper bound confusion occur?

Upper bound confusion can occur due to a variety of reasons, such as unclear definitions or assumptions, lack of knowledge or understanding about the problem or variable, or incorrect use of mathematical notation.

Why is it important to address upper bound confusion?

Addressing upper bound confusion is important because it can lead to incorrect or misleading results in scientific research or computer programming. It can also make it difficult to compare and interpret data or communicate results effectively.

How can upper bound confusion be resolved?

To resolve upper bound confusion, it is important to carefully define all variables and parameters, use clear and consistent notation, and double-check all calculations and assumptions. Communicating clearly with others and seeking clarification when necessary can also help prevent upper bound confusion.

Can upper bound confusion be completely eliminated?

While it may not be possible to completely eliminate upper bound confusion, it can be minimized by following best practices in scientific research and programming, such as thorough testing and peer review, and being aware of common sources of confusion. It is also important to continuously reflect on and improve upon one's own understanding and methods to prevent and address upper bound confusion.

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