Applications of Differentiation

Applications of Differentiation

Maximum and Minimum Values

Some of the most important applications of differential calculus are optimization problems, in which we are required to find the optimal (best) way of doing something.

Absolute and Local Extreme Values

Absolute Values

Let $c$ bea a number in the domain $D$ of a function $f$. Then $f(c)$ is the

  • absolute maximum value of $f$ on $D$ if $f(c) \geq f(x)$ for all $x$ in $D$
  • absolute minimum value of $f$ on $D$ if $f(c) \leq f(x)$ for all $x$ in $D$

An absolute maximum or minimum is sometimes called a global maximum or minimum. The maximum and minimum values of $f$ are called extreme values of $f$.

The Extreme Value Theorem

If $f$ is continuous on a closed interval $[a, b]$, then $f$ attains an absolute maximum value $f(c)$ and an absolute minimum value $f(d)$ at some numbers $c$ and $d$ in $[a, b]$.

The Extreme Value Theorem is illustrated in Figure 8.

Extreme Value Theorem

Critical Numbers and the Closed Interval Method

Fermat’s Theorem

If $f$ has a local maximum or minimum at $c$, and if $f’(c)$ exists, then $f’(c) = 0$.

PROOF: Suppose that $f$ has a local maximum at $c$. Then accoding to the definition of a local maximum $f(c) \geq f(x)$ if $x$ is sufficiently close to $c$. This implies that if $h$ is sufficiently close to $0$, with $h$ being positive or negative, then:

$$ f(c) \geq f(c + h) $$

and therefore

$$ f(c + h) - f(c) \leq 0 $$

We can divide both sides of an inequality by a positive number $h$, then

$$ \frac{f(c + h) - f(c)}{h} \leq 0 $$

Taking the right-hand limit of both sides we get

$$ \lim_{h \rightarrow 0^+} \frac{f(c + h) - f(c)}{h} \leq \lim_{h \rightarrow 0^+} = 0 $$

Since $f’(0)$ exists, we have

$$ \lim_{h \rightarrow 0} \frac{f(c + h) - f(c)}{h} = \lim_{h \rightarrow 0^+} \frac{f(c + h) - f(c)}{h} $$

and so we have shown that $f’(c) \leq 0$. If $h < 0$, then

$$ \frac{f(c + h) - f(c)}{h} \geq 0 $$

So taking the left-hand limit, we have

$$ \lim_{h \rightarrow 0} \frac{f(c + h) - f(c)}{h} = \lim_{h \rightarrow 0^-} \frac{f(c + h) - f(c)}{h} \geq 0 $$

We have shown that $f’(c) \geq 0$ and $f’(c) \leq 0$ so the only possibility is that $f’(c) = 0$.

We can’t expect to locate extreme values simply by setting $f’(x) = 0$ and solving for $x$. The fact that $f’(x) = 0$ simply means that the curve $f$ has a horizontal tangent at $(x, f(x))$. In other words, the converse of Fermat’s Theorem is false in general. However, Fermat’s Theorem does suggest that we should at least start looking for extreme values of $f$ at the number $c$ where $f’(c) = 0$ or where $f’(c)$ does not exist.

Critical Number

A critical number of a function $f$ is a number $c$ in the domain of $f$ such that either $f’(c) = 0$ or $f’(c)$ does not exist.

In terms of critical numbers, Fermat’s Theorem can be rephared as follows:

Fermat’s Theorem

If $f$ has a local maximum of minimum at $c$, then $c$ is a critical number of $f$.

The Closed Interval Method

To find the absolute maximum and minimum values of a continuous function $f$ on a closed interval $[a, b]$:

  1. Find the values of $f$ at the critical numbers of $f$ in $(a, b)$
  2. Find the values of $f$ at the endpoints of the interval.
  3. The largest of the values from Steps 1 and 2 is the absolute maximum value; the samllest of these values is the absolute minimum value.

The Mean Value Theorem

Rolle’s Theorem

Rolle’s Theorem

Let $f$ be a function that satisfies the following three hypotheses:

  1. $f$ is continuous on the closed interval $[a, b]$
  2. $f$ is differentiable on the open interval $(a, b)$
  3. $f(a) = f(b)$

The there is a number $c$ in $(a, b)$ such that $f’(c) = 0$

PROOF: There are three cases:

Case 1 $f(x) = k$, a constant. Then $f’(x) = 0$, so the number $c$ can be taken to be any numer in $(a, b)$.

Case 2 $f(x) > f(a)$ for some $x \in (a, b)$. Then, by the Extreme Value Theorem (which we can apply by hypothesis 1), $f$ has a maximum value somewhere in $[a, b]$. Since $f(a) = f(b)$ it must attain this maximum value at a number $c$ in the open interval $(a, b)$. Then $f$ has a local maximum at $c$, and by hypothesis 2, $f$ is differentiable at $c$. Therefore $f’(c) = 0$ by Fermat’s Theorem.

Case 3 $f(x) < f(a)$ for some $x \in (a, b)$. Then, by the Extreme Value Theorem (which we can apply by hypothesis 1), $f$ has a minimum value somewhere in $[a, b]$. Since $f(a) = f(b)$ it must attain this minimum value at a number $c$ in the open interval $(a, b)$. Then $f$ has a local minimum at $c$, and by hypothesis 2, $f$ is differentiable at $c$. Therefore $f’(c) = 0$ by Fermat’s Theorem.

Figure 1 shows the graphs of four such functions.

Rolles Theorem

The Mean Value Theorem

The Mean Value Theorem

Let $f$ be a function that satisfies:

  1. $f$ is continuous on the closed interval $[a, b]$
  2. $f$ is differentiable on the open interval $(a, b)$

The there is a number $c$ in $(a, b)$ such that

$$f'(c) = \frac{f(b) - f(a)}{b - a}$$

or equivalently

$$f(b) - f(a) = f'(c)(b - a)$$

The Mean Value Theorem says that there is at least one point $P(c, f(c))$ on the graph where the slope of the tangent line is the same as the slope of the secant line $A, B$ (see Figures 3 and 4).

Mean Value Theorem

PROOF We see the the equation of the line $AB$ can be written as:

$$ y - f(a) = m_{AB} (x - a) $$

where $m_{AB} = \frac{f(b) - f(a)}{b - a}$, thus

$$ y = f(a) + \frac{f(b) - f(a)}{b - a}(x - a) $$

Mean Value Theorem Proof

So, as we can see on Figure 5:

$$ h(x) = f(x) - y $$$$ h(x) = f(x) - f(a) - \frac{f(b) - f(a)}{b - a}(x - a) $$

First, we must verify that $h$ satisfies the three hypotheses of Rolle’s Theorem:

  1. The function $h$ is continuous on $[a, b]$ because it is the sum of $f$ and a first-degree polynomial both of which are continuous.
  2. The function $h$ is differentiable because both $f$ and the first degree polynomial are differentiable. Thus
$$ h'(x) = f'(x) - \frac{f(b) - f(a)}{b - a} $$
  1. We must show that $h(a) = h(b)$
$$ h(a) = f(a) - f(a) - \frac{f(b) - f(a)}{b - a}(a - a) = 0 $$$$ h(b) = f(b) - f(a) - \frac{f(b) - f(a)}{b - a}(b - a) $$$$ = f(b) - f(a) - f(b) + f(a) = 0 $$

Which means $h(a) = h(b) = 0$.

Since $h$ satisfies all the hypotheses of Rolle’s Theorem, there exists a number $c$ in $(a, b)$ such that $h’(c) = 0$. Therefore

$$ h'(c) = f'(c) - \frac{f(b) - f(a)}{b - a} = 0 $$

So

$$ f'(c) = \frac{f(b) - f(a)}{b - a} $$

In general, the Mean Value Theorem can be interpreted as saying that there is a number at which the instantaneous rate of change is equal to the average rate of change over an interval.

The Mean Value Theorem can be used to establish some of the basic facts of differential calculus.

Theorem

If $f’(x) = 0$ for all $x$ in an interval $(a, b)$, then $f$ is constant on $(a, b)$

PROOF: Let $x_1$ and $x_2$ be any two numbers in $(a, b)$ with $x_1 < x_2$. Since $f$ is differentiable on $(a, b)$ it must be differentiable on $(x_1, x_2)$ and continuous on $[x_1, x_2]$. By applying the Mean Value Theorem to $f$ on the interval $[x_1, x_2]$, we get a number $c$ such that $x_1 < c < x_2$ and

$$ f(x_2) - f(x_1) = f'(c) (x_2 - x_1) $$

Since $f’(x) = 0$ for all $x$, then $f’(c) = 0$ and therefore

$$ f(x_2) - f(x_1) = 0 \leftrightarrow f(x_2) = f(x_1) $$

Thus $f$ has the same value at any two numbers $x_1$ and $x_2$ in $(a, b)$. This means that $f$ is constant on $(a, b)$.

Corollary

If $f’(x) = g’(x)$ for all $x$ in an interval $(a, b)$, then $f - g$ is constant on $(a, b)$; that is, $f(x) = g(x) + c$ where $c$ is a constant.

PROOF: Let $F(x) = f(x) - g(x)$. Then

$$ F'(x) = f'(x) - g'(x) = 0 $$

for all $x \in (a, b)$. Thus by the previous theorem $F$ is constant, that is $f - g$ is constant.

This corollary says that if two functions have the same derivatives on an interval, then their graphs must be vertical trasnlation of each other.

What Derivatives Tell Us about the Shape of a Graph

What Does $f’$ say about $f$?

Increasing/Decreasing Test

If $f’(x) > 0$ on an interval, then $f$ is increasing on that interval

If $f’(x) < 0$ on an interval, then $f$ is decreasin on that interval

See Figure 1 for a graphical representation.

Increasing/Decreasing Test

PROOF: Without loss of generality we let $x_1$ and $x_2$ be any two numbers on the interval with $x_1 < x_2$. According to the definition of an increasing function we have to show that $f(x_1) < f(x_2)$.

Because we are given that $f’(x) > 0$, we know that $f$ is differentiable on $[x_1, x_2]$. So, by the Mean Value Theorem, there is a number $c$ between $x_1$ and $x_2$ such that

$$ f(x_2) - f(x_1) = f'(c)(x_2 - x_1) $$

We know that $f’(c) > 0$ by our initial assumption and $x_2 - x_1$ because $x_1 < x_2$, thus the right side of the previous equation must be positive:

$$ f(x_2) - f(x_1) > 0 $$

Which is equivalent to

$$ f(x_2) > f(x_1) $$

This shows that $f$ is increasing.

The First Derivative Test

The First Derivative Test

Suppose $c$ is a critical number of a continuous function $f$.

  1. If $f’$ changes from positive to negative at $c$, then $f$ has a local maximum at $c$
  2. If $f’$ changes from negative to positive at $c$, then $f$ has a local minimum at $c$
  3. If $f’$ is positive to the left and right of $c$, or negative to the left and right of $c$ then $f$ has no local maximum or minimum at $c$

The First Derivative Test is illustrated in Figure 4.

The First Derivative Test

What does $f’’$ say about $f’$?

Concavity of a Function

If the graph of $f$ lies above all of its tangents on an interval $I$, then $f$ is called concave upward on $I$.

If the graph of $f$ lies below all of its tangents on an interval $I$, then $f$ is called concave downward on $I$.

See Figure 7 for an illustration on the concavity of a function.

Concavity of a Function

In Figure 7(a) we see that the slope of the tangent increases. This means that the derivative $f’$ is an increasing function and therefore its derivative $f’’$ is positive. Likewise, in Figure 7(b) the slope of the tangent decreases, so $f’$ decreases and therefore $f’’$ is negative.

Concavity Test

  1. If $f’’(x) > 0$ on an interval $I$, then the graph of $f$ is concave upward on $I$.
  2. If $f’’(x) < 0$ on an interval $I$, then the graph of $f$ is concave downward on $I$.

Inflection Point

A point $P$ on a curve $y = f(x)$ is called an inflection point if $f$ is continuous there and the curve changes from concave upward to concave downward or viceversa.

The Second Derivative Test

The Second Derivative Test

Suppose $f’’$ is continuous near $c$

  1. If $f’(c) = 0$ and $f’’(c) > 0$, then $f$ has a local minimum at $c$
  2. If $f’(c) = 0$ and $f’’(c) < 0$, then $f$ has a local maximum at $c$

Note that The Second Derivative Test is inconclusive when $f’’(c) = 0$ as there might be a maximum, a minimum or neither in that point. This test also fails when $f’’(c)$ does not exist.

Indeterminate Forms and l’Hospital’s Rule

Indeterminate Forms (Types $\frac{\infty}{\infty}$, $\frac{0}{0}$)

In general, if we have a limit of the form:

$$ \lim_{x \to a} \frac{f(x)}{g(x)} $$

where both $f(x) \to 0$ and $g(x) \to 0$ as $x \to a$, then this limit may or may not exist, and is called an indeterminate form of type $\frac{0}{0}$.

In general, if we have a limit of the form:

$$ \lim_{x \to a} \frac{f(a)}{g(a)} $$

where both $f(x) \to \infty$ (or $-\infty$) and $g(x) \to \infty$ (or $-\infty$) as $x \to a$, then this limit may or may not exist, and is called an indeterminate form of type $\frac{\infty}{\infty}$.

L’Hospital’s Rule

We introduce a systematic method for the evaluation of indeterminate forms of type $\frac{0}{0}$ or type $\frac{\infty}{\infty}$.

L’Hospital’s Rule

Suppose $f$ and $g$ are differentiable and $g’(x) \neq 0$ on an open interval $I$ that contains $a$ (except possibly at $a$). Suppose that:

$$\lim_{x \to a} f(x) = 0 \text{ and } \lim_{x \to a} g(x) = 0$$

or that

$$\lim_{x \to a} f(x) = \pm \infty \text{ and } \lim_{x \to a} g(x) = \pm \infty$$

So we have an indeterminate form of type $\frac{0}{0}$ or $\frac{\infty}{\infty}$. Then:

$$\lim_{x \to a} \frac{f(x)}{g(x)} = \lim_{x \to a} \frac{f'(x)}{g'(x)}$$

if the limit on the right side exists (or is $\infty$ or $-\infty$)

Note:

  1. L’Hospital’s Rule says that the limit of a quotient of function is equal to the limit of the quotient of their derivatives, provided that the conditions are satisfied.
  2. L’Hospital’s Rule is also valid for one-sided limit, and for limits at infinity or negative infinity.
  3. For the special case in which $f(a) = g(a) = 0$, $f’$ and $g’$ are continuous and $g’(a) \neq 0$, it is easy to show why l’Hospital’s Rule is true:

Given $f’$ and $g’$ are continuous:

$$ \lim_{x \to a} \frac{f'(x)}{g'(x)} = \frac{f'(a)}{g'(a)} $$

By the definition of a derivative:

$$ \frac{f'(a)}{g'(a)} = \frac{\lim_{x \to a} \frac{f(x) - f(a)}{x - a}}{\lim_{x \to a} \frac{g(x) - g(a)}{x - a}} $$

By the properties of limits:

$$ \frac{\lim_{x \to a} \frac{f(x) - f(a)}{x - a}}{\lim_{x \to a} \frac{g(x) - g(a)}{x - a}} = \lim_{x \to a} \frac{\frac{f(x) - f(a)}{x - a}}{ \frac{g(x) - g(a)}{x - a}} $$$$ \lim_{x \to a} \frac{\frac{f(x) - f(a)}{x - a}}{ \frac{g(x) - g(a)}{x - a}} = \lim_{x \to a} \frac{f(x) - f(a)}{g(x) - g(a)} $$

Because $f(a) = g(a) = 0$

$$ \lim_{x \to a} \frac{f(x) - f(a)}{g(x) - g(a)} = \lim_{x \to a} \frac{f(x)}{g(x)} $$

It is more difficult to prove the general version of l’Hospital’s Rule.

Indeterminate Products (Type $0 \cdot \infty$)

If $\lim_{x \to a} f(x) = 0$ and $\lim_{x \to a} g(x) = \infty$ or ($- \infty$), then it isn’t clear what the value of $\lim_{x \to a} [f(x)g(x)]$ will be.

This kind of limit is called an indeterminate form of type $0 \cdot \infty$. We can deal with it by writing the product $fg$ as a quotient:

$$ fg = \frac{f}{\frac{1}{g}} \text{ or } fg = \frac{g}{\frac{1}{f}} $$

This converts the given limit into an indeterminate form of type $\frac{0}{0}$ or $\frac{\infty}{\infty}$ so that we can use l’Hospital’s Rule.

Indeterminate Differences (Type $\infty - \infty$)

If $\lim_{x \to a} f(x) = \infty$ and $\lim_{x \to a} g(x) = \infty$, then the limit:

$$ \lim_{x \to a} [f(x) - g(x)] $$

is called an indeterminate form of type $\infty - \infty$. There is a contest between $f$ and $g$. Will the answer be $\infty$ ($f$ wins), $-\infty$ ($g$ wins) or will they compromise on a finite number? To find out, we try to convert the difference into a quotient so that we can have an indeterminate form of type $\frac{0}{0}$ or $\frac{\infty}{\infty}$.

Indeterminate Powers (Types $0^0, \infty^0, 1^{\infty}$)

Several indeterminate forms arise from the limit:

$$ \lim_{x \to a} [f(x)]^{g(x)} $$
  1. $\lim_{x \to a} f(x) = 0$ and $\lim_{x \to a} g(x) = 0$, type $0^0$
  2. $\lim_{x \to a} f(x) = \infty$ and $\lim_{x \to a} g(x) = 0$, type $\infty^0$
  3. $\lim_{x \to a} f(x) = 1$ and $\lim_{x \to a} g(x) = \pm \infty$, type $1^{\infty}$

Each of these three cases can be treated by taking the natural logarithm as follows:

$$ \text{let } y = [f(x)]^{g(x)} \text{, then } \ln y = g(x) \ln f(x) $$

Now we calculate:

$$ \lim_{x \to a} g(x) \ln f(x) $$

This limit is always an indeterminate product (indeterminate form of type $0 \cdot \infty$), and can be solved as one, which will require the application of L’Hospital’s Rule.

Once we get the value of the limit for $\ln y$, we can obtain the limit of $y$ by writing the logarithm of $y$ as an exponential:

$$ \lim_{x \to a} y = \lim_{x \to a} [f(x)]^{g(x)} = \lim_{x \to a} e^{\ln y} = \lim_{x \to a} e^{g(x) \ln f(x)} = e^{\lim_{x \to a} g(x) \ln f(x)} $$