The definition of the derivative of a function is given next. We start with an example illustrating the idea behind the formal definition.
Example 0.
The graph below shows how far a cyclist gets from his starting point.
a) Look at the red line. We can see that in three hours, the cyclist moved km. The average speed of the whole trip is km/h.
b) Now look at the green line. We can see that during the third hour the cyclist moved km further. That makes the average speed of that time interval km/h.
Notice that the slope of the red line is and that the slope of the blue line is . These are the same values as the corresponding average speeds.
c) Look at the blue line. It is the tangent of the curve at the point . Using the same principle as with average speeds, we conclude that after two hours of the departure, the speed of the cyclist was km/h km/h.
Now we will proceed to the general definition:
Definition: Derivative
Let . The derivative of function at the point is If exists, then is said to be differentiable at the point .
Note: Since , then , and thus the definition can also be written in the form
The derivative can be denoted in different ways:
Interpretation. Consider the curve . Now if we draw a line through the points and , we see that the slope of this line is When , the line intersects with the curve only in the point . This line is the tangent of the curve at the point and its slope is which is the derivative of the function at . Hence, the tangent is given by the equation
Interactivity. Move the point of intersection and observe changes on the tangent line of the curve.
Here is the slope of the tangent line. Note that the derivative at does not depend on because is the equation of a line.
Note. When , we get and . The derivative of a constant function is zero.
Example 3.
Let be the function . Does have a derivative at ?
Now
The graph has no tangent at the point : Thus does not exist.
Conclusion. The function is not differentiable at the point .
Remark. Let . If exists for every then we get a function . We write:
(1)
= ,
(2)
=
= ,
(3)
=
= ,
(4)
=
= ,
...
Here is called the second derivative of at , is the third derivative, and so on.
We introduce the notation \begin{eqnarray} C^n\bigl( ]a,b[\bigr) =\{ f\colon \, ]a,b[\, \to \mathbb{R} & \mid & f \text{ is } n \text{ times differentiable on the interval } ]a,b[ \nonumber \\ & & \text{ and } f^{(n)} \text{ is continuous}\}. \nonumber \end{eqnarray} These functions are said to be n times continuously differentiable.
Example 4.
The distance moved by a cyclist (or a car) is given by . Then the speed at the moment is and the acceleration is .
Linearization and differential
Derivative can also be used to approximate functions. From the definition of the derivative, we get where the right-handed side is the linearization or the differential of at . The differential is denoted by . The graph of the linearization, is the tangent line drawn on the graph of the function at the point . Later, in multi-variable calculus, the true meaning of the differential becomes clear. For now, it is not necessary to get troubled by the details.
Properties of derivative
Next we give some useful properties of the derivative. These properties allow us to find derivatives for some familiar classes of functions such as polynomials and rational functions.
Continuity and derivative
If is differentiable at the point , then is continuous at the point : Why? Because if is differentiable, then we get as .
Note. If a function is continuous at the point , it doesn't have to be differentiable at that point. For example, the function is continuous, but not differentiable at the point .
Differentiation Rules
Next we will give some important rules which are often applied in practical problems concerning determination of the derivative of a given function.
The one-sided limits of the difference quotient have different signs at a local extremum. For example, for a local maximum it holds that \begin{eqnarray} \frac{f(x_0+h)-f(x_0)}{h} = \frac{\text{negative} }{\text{positive}}&\le& 0, \text{ when } h>0, \nonumber \\ \frac{f(x_0+h)-f(x_0)}{h} = \frac{\text{negative}}{\text{negative}}&\ge& 0, \text{ when } h<0 \nonumber \end{eqnarray} and is so small that is a maximum on the interval .
L'Hospital's Rule
There are many different versions of this rule, but we present only the simplest one. Let us assume that and the functions are differentiable on some interval . If exists, then
In the special case the proof is simple: In the general case we need the so-called generalized mean value theorem, which states that for some . Here we have the same point both in the numerator and the denominator, so we do not even need the continuity of the derivatives!
Derivatives of Trigonometric Functions
In this section, we give differentiation formulas for trigonometric functions , and .
This follows in a similar way as the derivative of Sine, but more easily from the identity and the Chain rule to be introduced in the following section.
Problem. What if ? Note that one cannot divide by zero.
Solution. Define
so that
Now, because is continuous, we get
as .
Example 1.
The problem is to differentiate the function . We take and and differentiate the composite function . As
we get
Example 2.
We need to differentiate the function . Take and , then differentiate the composite function .
Remark. Let and . Now
Similarly, one may obtain even more complex rules for composites of multiple functions.
Example 3.
Differentiate the function . Take , and and differentiate the composite function .
Extremal Value Problems
We will discuss the Intermediate Value Theorem for differentiable functions, and its connections to extremal value problems.
Definition: Local Maxima and Minima
A function has a a local maximum at the point , if for some and for all such that , we have .
Similarly, a function has a local minimum at the point , if for some and for all such that , we have .
A local extreme is a local maximum or a local minimum.
Remark. If is a local maximum value and exists, then
Hence .
We get:
Theorem 1.
Let be a local extremal value of a continuous function . Then either
the derivative doesn't exist (this includes also cases and ) or
.
Example 1.
Let be defined by
Then
and we can see that at the points and the local maximum and minimum of are obtained,
Finding the global extrema
In practice, when we are looking for the local extrema of a given function, we need to check three kinds of points:
the zeros of the derivative
the endpoints of the domain of definition (interval)
points where the function is not differentiable
If we happened to know beforehand that the function has a minimum/maximum, then we start off by finding all the possible local extrema (the points described above), evaluate the function at these points and pick the greatest/smallest of these values.
Example 2.
Let us find the smallest and greatest value of the function , . Since the function is continuous on a closed interval, then it has a maximum and a minimum. Since the function is differentiable, it is sufficient to examine the endpoints of the interval and the zeros of the derivative that are contained in the interval.
The zeros of the derivative: .
Since , we only need to evaluate the function at three points, , and . From these we can see that the smallest value of the function is and the greatest value is , respectively.
Next we will formulate a fundamental result for differentiable functions. The basic idea here is that the change on an interval can only happen, if there is change at some point on the inverval.
Theorem 2.
(The Intermediate Value Theorem for Differentiable Functions). Let be continuous in the interval and differentiable in the interval . Then
for some
Hence we may conclude that is increasing for and decreasing for .
Example 3.
For the polynomial the derivative is
when , or . Now we can draw a table:
decr.
incr.
decr.
incr.
Example 4.
We need to find a rectangle so that its area is and it has the least possible perimeter.
Let and be the sides of the rectangle. Then and we get . Now the perimeter is
In which point does the function get its minimum value? Function is continuous and differentiable, when and using the quotient rule, we get
Now , when
but we have defined that and therefore are only interested in the case . Let's draw a table:
decr.
incr.
As the function is continuous, we now know that it attains its minimum at the point . Now we calculate the other side of the rectangle: .
Thus, the rectangle, which has the least possible perimeter is actually a square, which sides are of the length .
Example 5.
We must make a one litre measure, which is shaped as a right circular cylinder without a lid. The problem is to find the best size of the bottom and the height so that we need the least possible amount of material to make the measure.
Let be the radius and the height of the cylinder. The volume of the cylinder is dm and we can write from which we get
The amount of material needed is the surface area
Let function be defined by
We must find the minimum value for function , which is continuous and differentiable, when . Using the reciprocal rule, we get
Now , when
Let's draw a table:
decr.
incr.
As the function is continuous, we now know that it gets its minimum value at the point . Then
This means that it would take least materials to make a measure, which is approximately dm dm cm in diameter and dm cm high.