How do derivatives provide answers for optimization problems ?

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Discussion Overview

The discussion revolves around the role of derivatives in solving optimization problems, particularly in the context of maximizing area with a fixed perimeter, such as using 500 meters of fencing. Participants explore the relationship between derivatives and optimization, including the conditions for identifying maximum and minimum values.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning

Main Points Raised

  • One participant expresses a basic understanding of calculus and seeks clarification on how derivatives relate to optimization problems, specifically in maximizing area with a fixed perimeter.
  • Another participant notes that the slope of a curve at maximum or minimum points is zero, indicating that the derivative of the function is zero at these points.
  • A participant provides a specific example involving the area of a rectangle with a perimeter constraint, explaining how to express the area as a function of one variable and the significance of the derivative in finding maximum area.
  • Further clarification is offered regarding the implications of positive and negative derivatives, explaining how they relate to increasing and decreasing function values, and emphasizing that a maximum or minimum occurs where the derivative is zero.
  • It is noted that having a derivative of zero is a necessary condition for identifying extrema, but not sufficient, as illustrated by the example of the function y = x^3, where the derivative is zero but does not correspond to a maximum or minimum.

Areas of Agreement / Disagreement

Participants generally agree on the role of derivatives in identifying maximum and minimum points in optimization problems, but there is no consensus on the sufficiency of the conditions for extrema, as highlighted by the example provided.

Contextual Notes

The discussion includes assumptions about the nature of functions and their derivatives, as well as the specific conditions under which optimization occurs. The example provided may depend on the definitions of maximum and minimum in the context of calculus.

urbano
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I' at a a very very very basic level of calculus and usually have to watch a video or read something basic just to understand the basics.

I'm fascinated by optimization equations, for example what is the largest area that can made with 500m of fencing. So at some point in solving this we end up using the first derivative.

My limited understanding of first derivatives however relates to finding the slope of of a point on a curve.

What I am currently struggling to understand is how does finding the slope on a point of a curve relate to finding the maximum area that can be created with a certain amount of fencing?

thanks in advance for any help with this
 
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The slope of a curve at a maximum or minimum is zero, hence the derivative of the function is zero at these points.
 
Consider an area with sides of length a and b so that 2(a+b) =500. The area is given by ab and by substitution a(250-a). If you plot the graph of area (on the y axis) as a function of a (on the x axis) will get a curve:
Y = 250x -x^2 which will increase initially and them start to fall.
You are trying to find the point where the area is a maximum and that will when y is a maximum. The gradient of the curve at that point will be zero.
 
If the derivative at a point is positive the function value is increasing- increasing x slightly will give a higher value so the point is not a maximum, decreasing x slightly will give a lower value so the point is not a minimum.

If the derivative at a point is negative the function value is decreasing- increasing x slightly will give a lower value so the point is not a minimum, decreasing x slightly will give a higher value so the point is not a maximum.

A maximum or minimum can only occur where the derivative is 0.

But note that this is a "necessary condition", not a "sufficient condition". The derivative of y= x^3, 3x^2, is 0 at x= 0 but there is neither maximum nor minimum there.
 

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