Proving the Existence of a Maximum or Minimum for a Continuous Function

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In summary, to prove that a continuous function f(x) has a maximum or minimum in R, we can use the Weierstrass theorem. This theorem states that for any interval [M1, M2], the function will have a maximum and minimum value. By considering the intervals [M1, M3], [M2, M3], we can see that the maximum value in the first interval will not be greater than the maximum value in the second interval. However, it is not clear how to handle the minimum values in this way. An alternative approach is to take the supremum (sup) of the function and show that it is finite. If the sup is greater than L, we can then show that
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i have a continuous function f:R->R and we are given that lim f(x)=L as x approaches infinity and limf(x)=L as x approaches minus infinity, i need to prove that f gets a maximum or minimum in R.

obviously i need to use weirstrauss theorem, but how to implement it in here.
i mean by defintion:
Ae>0,EM_e,Ax>=M_e, |f(x)-L|<e
Ae>0,Em_e,Ax<=m_e,|f(x)-L|<e

so if we look at the intervals:
[M1,M2],[M1,M3]...
[m2,m1],[m3,m1]...
in each interval the function gets a maximum and minimum by the theorem i quoted above, at the capital M's as x ais bigger than M1 its interval of f is increased i.e for x>=M1 L-1<f(x)<L+1 for x >=M2 L-2<f(x)<L+2 so it means the maximum in the first interval isn't bigger than the maximum in the second interval (the problem is i cannot say the same about the minimum).
now if f has a maximum then we finished if it doesn't then i should show it has a minimum, but if it doesn't have a maximum then each maximum in the intervals is bigger than the previous one, but we have that there isn't a maximum.
here I am stuck and i don't know how to procceed from here, any help will be appreciated.
 
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I don't understand your method. Why would it treat maxima any different than minima?

Here's how I would do it. You can always take the sup of a function. Show the sup of this function is finite. If it's greater than L, find a way to show the function must actually attain this value, making it a max. You can go from here.
 
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What is the definition of continuity?

Continuity is a concept in mathematics and physics that describes a smooth and unbroken connection between two points or values. In simpler terms, it means that there are no sudden or abrupt changes, but rather a gradual and continuous transition.

How is continuity different from differentiability?

Continuity and differentiability are related concepts, but they have different definitions. Continuity refers to a smooth and unbroken connection between two points, while differentiability refers to the existence of a derivative at a certain point. In other words, a function can be continuous but not differentiable, but if a function is differentiable at a point, it must also be continuous at that point.

What are the three types of continuity?

The three types of continuity are point continuity, interval continuity, and uniform continuity. Point continuity refers to a function being continuous at a specific point, interval continuity refers to a function being continuous on a specific interval, and uniform continuity refers to a function being continuous on a whole domain.

How can continuity be tested?

Continuity can be tested using the three-part continuity test, which includes checking for the existence of a limit at a point, checking if the function is defined at that point, and checking if the limit equals the function value at that point. Another way to test continuity is by visually inspecting the graph of the function for any sudden breaks or holes.

Why is continuity important in mathematics and physics?

Continuity is essential in mathematics and physics because it allows us to make predictions and analyze the behavior of functions and physical phenomena. It helps us to understand how values change over time or distance and to make connections between different points or values. Additionally, continuity is a fundamental concept in calculus and is used in various applications, such as optimization and modeling real-world situations.

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