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Calculus
For Computer Science @ BUKC
Topics* for Week 4 (Lecture 2)
•Derivative; How to compute
Derivative
The Derivative as a Function
We have considered the derivative of a function f at a fixed
number a:
Here we change our point of view and let the number a vary. If
we replace a in Equation 1 by a variable x, we obtain
The Derivative as a Function
The Derivative as a Function
Given any number x for which this limit exists, we assign
to x the number f′(x). So we can regard f′ as a new function,
called the derivative of f and defined by Equation 2.
We know that the value of f′ at x, f′(x), can be interpreted
geometrically as the slope of the tangent line to the graph
of f at the point (x, f(x)).
The function f′ is called the derivative of f because it has
been “derived” from f by the limiting operation in Equation 2.
The domain of f′ is the set {x|f′(x) exists} and may be
smaller than the domain of f.
Example 1
The graph of a function f is given in Figure 1. Use it to
sketch the graph of the derivative f .
′
Figure 1
Example 1 – Solution
We can estimate the value of
the derivative at any value of
x by drawing the tangent at the
point (x, f(x)) and estimating
its slope. For instance, for x = 5
we draw the tangent at P in
Figure 2(a) and estimate its
slope to be about ,
so f (5)
′  1.5.
Figure 2
Example 1 – Solution
This allows us to plot the point
P (5, 1.5) on the graph of
′ f′
directly beneath P. Repeating this
procedure at several points,
we get the graph shown
in Figure 2(b).
Figure 2
cont’d
Example 1 – Solution
Notice that the tangents at A, B, and C are horizontal, so the
derivative is 0 there and the graph of f crosses the
′
x-axis (where y = 0) at the points A ,
′ B , and
′ C , directly beneath
′
A, B, and C.
Between A and B the tangents have positive slope, so f (
′ x) is
positive there. But between B and C the tangents have negative
slope, so f (
′ x) is negative there.
cont’d
The Derivative as a Function
When x is close to 0, is also close to 0, so
f (
′ x) = 1/(2 ) is very large and this corresponds to the steep
tangent lines near (0, 0) in Figure 4(a) and the large values of f′
(x) just to the right of 0 in Figure 4(b).
Figure 4
The Derivative as a Function
When x is large, f (
′ x) is very small and this corresponds to the
flatter tangent lines at the far right of the graph of f and the
horizontal asymptote of the graph of f .
′
Other Notations
Other Notations
If we use the traditional notation y = f(x) to indicate that the
independent variable is x and the dependent variable is y, then
some common alternative notations for the derivative are as
follows:
The symbols D and d/dx are called differentiation operators
because they indicate the operation of differentiation, which is
the process of calculating a derivative.
Other Notations
The symbol dy/dx, which was introduced by Leibniz, should not
be regarded as a ratio (for the time being); it is simply a synonym
for f (
′ x). Nonetheless, it is a very useful and suggestive notation,
especially when used in conjunction with increment notation.
We can rewrite the definition of derivative in Leibniz notation in
the form
Other Notations
If we want to indicate the value of a derivative dy/dx in Leibniz
notation at a specific number a, we use the notation
which is a synonym for f (
′ a).
Where is the function f(x) = |x| differentiable?
Solution:
If x > 0, then |x| = x and we can choose h small enough that x +
h > 0 and hence |x + h| = x + h. Therefore, for
x > 0, we have
and so f is differentiable for any x > 0.
Example 5
Similarly, for x < 0 we have |x| = –x and h can be chosen small
enough that x + h < 0 and so |x + h| = –(x + h).
Therefore, for x < 0,
and so f is differentiable for any x < 0.
Example 5 – Solution cont’d
For x = 0 we have to investigate
Let’s compute the left and right limits separately:
and
Example 5 – Solution cont’d
Since these limits are different, f (0) does not exist. Thus
′ f is
differentiable at all x except 0.
A formula for f is given by
′
and its graph is shown in Figure 5(b).
Example 5 – Solution
Figure 5(b)
y = f(x)
cont’d
The fact that f (0) does not exist is reflected geometrically in the
′
fact that the curve y = |x| does not have a tangent line at (0, 0).
[See Figure 5(a).]
Example 5 – Solution
Figure 5(a)
y = f(x) = | x |
cont’d
Both continuity and differentiability are desirable properties for
a function to have. The following theorem shows how these
properties are related.
Note: The converse of Theorem 4 is false; that is, there are
functions that are continuous but not differentiable.
Other Notations
How Can a Function Fail to Be
Differentiable?
We saw that the function y = |x| in Example 5 is not
differentiable at 0 and Figure 5(a) shows that its graph changes
direction abruptly when x = 0.
In general, if the graph of a
function f has a “corner” or “kink”
in it, then the graph of f has no
tangent at this point and f is not
differentiable there. [In trying to
compute f (
′ a), we find that the
left and right limits are different.]
How Can a Function Fail to Be Differentiable?
Figure 5(a)
y = f(x) = | x |
Theorem 4 gives another way for a function not to have a
derivative. It says that if f is not continuous at a, then f is not
differentiable at a. So at any discontinuity (for instance, a jump
discontinuity) f fails to be differentiable.
A third possibility is that the curve has a vertical tangent line
when x = a; that is, f is continuous at a and
How Can a Function Fail to Be Differentiable?
This means that the tangent lines become steeper and steeper
as x  a. Figure 6 shows one way that this can happen; Figure
7(c) shows another.
Figure 6
How Can a Function Fail to Be Differentiable?
Figure 7(c)
A vertical tangent
Figure 7 illustrates the three possibilities that we have discussed.
Figure 7
Three ways for f not to be differentiable at a
How Can a Function Fail to Be Differentiable?
Higher Derivatives
If f is a differentiable function, then its derivative f is also a
′
function, so f may have a derivative of its own, denoted by (
′ f ) =
′ ′
f . This new function
′′ f is called the
′′ second derivative of f
because it is the derivative of the derivative of f.
Using Leibniz notation, we write the second derivative of
y = f(x) as
Higher Derivatives
If f(x) = x3
– x, find and interpret f (
′′ x).
Solution:
The first derivative of f(x) = x3
– x is f (
′ x) = 3x2
– 1.
So the second derivative is
Example 6
The graphs of f, f , and
′ f are shown in Figure 10.
′′
Example 6 – Solution
Figure 10
cont’d
We can interpret f (
′′ x) as the slope of the curve y = f (
′ x) at the
point (x, f (
′ x)). In other words, it is the rate of change of the
slope of the original curve y = f(x).
Notice from Figure 10 that f (
′′ x) is negative when y = f (
′ x) has
negative slope and positive when y = f (
′ x) has positive slope. So
the graphs serve as a check on our calculations.
Example 6 – Solution cont’d
In general, we can interpret a second derivative as a rate of
change of a rate of change. The most familiar example of this is
acceleration, which we define as follows.
If s = s(t) is the position function of an object that moves in a
straight line, we know that its first derivative represents the
velocity v(t) of the object as a function of time:
v(t) = s (
′ t) =
Higher Derivatives
The instantaneous rate of change of velocity with respect to time
is called the acceleration a(t) of the object. Thus the
acceleration function is the derivative of the velocity function
and is therefore the second derivative of the position function:
a(t) = v (
′ t) = s (
′′ t)
or, in Leibniz notation,
Higher Derivatives
The third derivative f′′′ is the derivative of the second derivative:
f = (
′′′ f ) . So
′′ ′ f (
′′′ x) can be interpreted as the slope of the curve y
= f (
′′ x) or as the rate of change of f (
′′ x).
If y = f(x), then alternative notations for the third derivative are
Higher Derivatives
We can also interpret the third derivative physically in the case
where the function is the position function s = s(t) of an object
that moves along a straight line.
Because s = (
′′′ s ) =
′′ ′ a , the third derivative of the position
′
function is the derivative of the acceleration function and is
called the jerk:
Higher Derivatives
Thus the jerk j is the rate of change of acceleration.
It is aptly named because a large jerk means a sudden change in
acceleration, which causes an abrupt movement in a vehicle.
Higher Derivatives
The differentiation process can be continued. The fourth
derivative f is usually denoted by
′′′′ f(4)
.
In general, the nth derivative of f is denoted by f(n)
and is
obtained from f by differentiating n times.
If y = f(x), we write
Higher Derivatives

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undergraduate course of calculus lecture slides

  • 2. Topics* for Week 4 (Lecture 2) •Derivative; How to compute
  • 4. The Derivative as a Function
  • 5. We have considered the derivative of a function f at a fixed number a: Here we change our point of view and let the number a vary. If we replace a in Equation 1 by a variable x, we obtain The Derivative as a Function
  • 6. The Derivative as a Function Given any number x for which this limit exists, we assign to x the number f′(x). So we can regard f′ as a new function, called the derivative of f and defined by Equation 2. We know that the value of f′ at x, f′(x), can be interpreted geometrically as the slope of the tangent line to the graph of f at the point (x, f(x)). The function f′ is called the derivative of f because it has been “derived” from f by the limiting operation in Equation 2. The domain of f′ is the set {x|f′(x) exists} and may be smaller than the domain of f.
  • 7. Example 1 The graph of a function f is given in Figure 1. Use it to sketch the graph of the derivative f . ′ Figure 1
  • 8. Example 1 – Solution We can estimate the value of the derivative at any value of x by drawing the tangent at the point (x, f(x)) and estimating its slope. For instance, for x = 5 we draw the tangent at P in Figure 2(a) and estimate its slope to be about , so f (5) ′  1.5. Figure 2
  • 9. Example 1 – Solution This allows us to plot the point P (5, 1.5) on the graph of ′ f′ directly beneath P. Repeating this procedure at several points, we get the graph shown in Figure 2(b). Figure 2 cont’d
  • 10. Example 1 – Solution Notice that the tangents at A, B, and C are horizontal, so the derivative is 0 there and the graph of f crosses the ′ x-axis (where y = 0) at the points A , ′ B , and ′ C , directly beneath ′ A, B, and C. Between A and B the tangents have positive slope, so f ( ′ x) is positive there. But between B and C the tangents have negative slope, so f ( ′ x) is negative there. cont’d
  • 11. The Derivative as a Function When x is close to 0, is also close to 0, so f ( ′ x) = 1/(2 ) is very large and this corresponds to the steep tangent lines near (0, 0) in Figure 4(a) and the large values of f′ (x) just to the right of 0 in Figure 4(b). Figure 4
  • 12. The Derivative as a Function When x is large, f ( ′ x) is very small and this corresponds to the flatter tangent lines at the far right of the graph of f and the horizontal asymptote of the graph of f . ′
  • 14. Other Notations If we use the traditional notation y = f(x) to indicate that the independent variable is x and the dependent variable is y, then some common alternative notations for the derivative are as follows: The symbols D and d/dx are called differentiation operators because they indicate the operation of differentiation, which is the process of calculating a derivative.
  • 15. Other Notations The symbol dy/dx, which was introduced by Leibniz, should not be regarded as a ratio (for the time being); it is simply a synonym for f ( ′ x). Nonetheless, it is a very useful and suggestive notation, especially when used in conjunction with increment notation. We can rewrite the definition of derivative in Leibniz notation in the form
  • 16. Other Notations If we want to indicate the value of a derivative dy/dx in Leibniz notation at a specific number a, we use the notation which is a synonym for f ( ′ a).
  • 17. Where is the function f(x) = |x| differentiable? Solution: If x > 0, then |x| = x and we can choose h small enough that x + h > 0 and hence |x + h| = x + h. Therefore, for x > 0, we have and so f is differentiable for any x > 0. Example 5
  • 18. Similarly, for x < 0 we have |x| = –x and h can be chosen small enough that x + h < 0 and so |x + h| = –(x + h). Therefore, for x < 0, and so f is differentiable for any x < 0. Example 5 – Solution cont’d
  • 19. For x = 0 we have to investigate Let’s compute the left and right limits separately: and Example 5 – Solution cont’d
  • 20. Since these limits are different, f (0) does not exist. Thus ′ f is differentiable at all x except 0. A formula for f is given by ′ and its graph is shown in Figure 5(b). Example 5 – Solution Figure 5(b) y = f(x) cont’d
  • 21. The fact that f (0) does not exist is reflected geometrically in the ′ fact that the curve y = |x| does not have a tangent line at (0, 0). [See Figure 5(a).] Example 5 – Solution Figure 5(a) y = f(x) = | x | cont’d
  • 22. Both continuity and differentiability are desirable properties for a function to have. The following theorem shows how these properties are related. Note: The converse of Theorem 4 is false; that is, there are functions that are continuous but not differentiable. Other Notations
  • 23. How Can a Function Fail to Be Differentiable?
  • 24. We saw that the function y = |x| in Example 5 is not differentiable at 0 and Figure 5(a) shows that its graph changes direction abruptly when x = 0. In general, if the graph of a function f has a “corner” or “kink” in it, then the graph of f has no tangent at this point and f is not differentiable there. [In trying to compute f ( ′ a), we find that the left and right limits are different.] How Can a Function Fail to Be Differentiable? Figure 5(a) y = f(x) = | x |
  • 25. Theorem 4 gives another way for a function not to have a derivative. It says that if f is not continuous at a, then f is not differentiable at a. So at any discontinuity (for instance, a jump discontinuity) f fails to be differentiable. A third possibility is that the curve has a vertical tangent line when x = a; that is, f is continuous at a and How Can a Function Fail to Be Differentiable?
  • 26. This means that the tangent lines become steeper and steeper as x  a. Figure 6 shows one way that this can happen; Figure 7(c) shows another. Figure 6 How Can a Function Fail to Be Differentiable? Figure 7(c) A vertical tangent
  • 27. Figure 7 illustrates the three possibilities that we have discussed. Figure 7 Three ways for f not to be differentiable at a How Can a Function Fail to Be Differentiable?
  • 29. If f is a differentiable function, then its derivative f is also a ′ function, so f may have a derivative of its own, denoted by ( ′ f ) = ′ ′ f . This new function ′′ f is called the ′′ second derivative of f because it is the derivative of the derivative of f. Using Leibniz notation, we write the second derivative of y = f(x) as Higher Derivatives
  • 30. If f(x) = x3 – x, find and interpret f ( ′′ x). Solution: The first derivative of f(x) = x3 – x is f ( ′ x) = 3x2 – 1. So the second derivative is Example 6
  • 31. The graphs of f, f , and ′ f are shown in Figure 10. ′′ Example 6 – Solution Figure 10 cont’d
  • 32. We can interpret f ( ′′ x) as the slope of the curve y = f ( ′ x) at the point (x, f ( ′ x)). In other words, it is the rate of change of the slope of the original curve y = f(x). Notice from Figure 10 that f ( ′′ x) is negative when y = f ( ′ x) has negative slope and positive when y = f ( ′ x) has positive slope. So the graphs serve as a check on our calculations. Example 6 – Solution cont’d
  • 33. In general, we can interpret a second derivative as a rate of change of a rate of change. The most familiar example of this is acceleration, which we define as follows. If s = s(t) is the position function of an object that moves in a straight line, we know that its first derivative represents the velocity v(t) of the object as a function of time: v(t) = s ( ′ t) = Higher Derivatives
  • 34. The instantaneous rate of change of velocity with respect to time is called the acceleration a(t) of the object. Thus the acceleration function is the derivative of the velocity function and is therefore the second derivative of the position function: a(t) = v ( ′ t) = s ( ′′ t) or, in Leibniz notation, Higher Derivatives
  • 35. The third derivative f′′′ is the derivative of the second derivative: f = ( ′′′ f ) . So ′′ ′ f ( ′′′ x) can be interpreted as the slope of the curve y = f ( ′′ x) or as the rate of change of f ( ′′ x). If y = f(x), then alternative notations for the third derivative are Higher Derivatives
  • 36. We can also interpret the third derivative physically in the case where the function is the position function s = s(t) of an object that moves along a straight line. Because s = ( ′′′ s ) = ′′ ′ a , the third derivative of the position ′ function is the derivative of the acceleration function and is called the jerk: Higher Derivatives
  • 37. Thus the jerk j is the rate of change of acceleration. It is aptly named because a large jerk means a sudden change in acceleration, which causes an abrupt movement in a vehicle. Higher Derivatives
  • 38. The differentiation process can be continued. The fourth derivative f is usually denoted by ′′′′ f(4) . In general, the nth derivative of f is denoted by f(n) and is obtained from f by differentiating n times. If y = f(x), we write Higher Derivatives