Mada za sehemu hiiDifferentiationMada 5
- Derivatives
- Differentiation of A Function
- Application Of Differentiation
- Taylor’s Series and Maclaurin’s Series
- Introduction to Partial Derivatives
Applications of differentiation
Differentiation has many real-world applications in various fields like science, engineering, economics, and more.
If (or ) is a small change in , and , then the corresponding small change in , denoted as (or ), can be approximated using the derivative:
Example 1
If , find an approximate change in when increases from 7 to 7.02.
Therefore, the approximate change in is 0.56.
Example 2
The side of a square is 10 cm. Find the increase in the area of the square when its side expands by 0.01 cm.
Let be the area and be the side length. Then .
cm
cm²
Therefore, the increase in area is approximately 0.2 cm².
Example 3
Use small changes to find an approximate value of .
Let . We know .
and
Example 4
If , where is a constant and an error of is made in measuring the radius . Prove that the resulting error in is .
Since the percentage error in is , we have .
Therefore, , which means the percentage error in is approximately .
The rate of change describes how one quantity changes with respect to another. In physics, the derivative of a position function with respect to time gives velocity, and the derivative of velocity gives acceleration.
Distance, velocity, and acceleration
If is the position of a particle at time , then:
- Velocity:
- Acceleration:
Also,
Example 1
The position of a particle is given by . Find the velocity and acceleration at seconds.
Velocity:
At , m/s.
Acceleration:
At , m/s².
Example 2
A particle moves along a line OB such that its distance from O is meters in seconds, where . Describe the motion at seconds.
Velocity:
Acceleration:
At :
-
Position: m (2m from O in the opposite direction from B)
-
Direction: Since m/s, the particle is moving towards O.
-
Speed: m/s.
-
Speed is increasing because the acceleration is positive and velocity is negative. The particle is moving towards O and speeding up.
-
Rate of change of speed (acceleration): m/s².
Example 3
A liquid is running out of a conical funnel at a rate of 5 cm³/s. The radius of the funnel is 10 cm and its height is 20 cm. How fast is the liquid level dropping when the liquid is 10 cm deep?
Let be the depth, the radius, and the volume. cm³/s.
By similar triangles, .
Volume of a cone:
Using the chain rule:
When :
cm/s.
Example 4
The volume of a spherical balloon increases at a constant rate of 1.5 cm³/s. When the volume is 62 cm³, find the rate of increase of its radius.
cm³/s.
When , cm.
Using the chain rule:
cm/s cm/s.
Turning points are points on a curve where the graph changes direction. A point of inflexion is a point where the curve changes its concavity (from concave up to concave down, or vice versa).
Turning points
A turning point occurs where the gradient of the curve is zero (i.e., ).
Steps to find turning points
- Differentiate the function to find .
- Set .
- Solve for . These are the x-coordinates of the turning points.
- Substitute the x-values back into the original function to find the corresponding y-coordinates.
Example 1
Find the coordinates of the turning point of .
Set :
Substitute into the original equation:
The turning point is .
Example 2
Determine the turning points of the curve .
Set :
Solving the quadratic equation (using factoring or the quadratic formula) gives and .
When :
When :
The turning points are and .
Example 3
Determine the turning points of the curve .
Set :
The discriminant of this quadratic is . Since the discriminant is negative, there are no real roots. Therefore, this curve has no turning points.
Points of inflexion
A point of inflexion occurs where the second derivative is zero and changes sign (i.e., ).
To find points of inflexion, you would typically:
- Find the second derivative, .
- Set and solve for .
- Check if the sign of changes around those x-values. If it does, those are x-coordinates of points of inflexion.
- Substitute the x-values back into the original function, , to find the corresponding y-coordinates.
Turning points (maximum, minimum, and points of inflexion) have various applications, including curve sketching and economic analysis (e.g., equilibrium prices, break-even points, marginal costs, and revenues).
Classifying stationary points
Here are the steps to find and classify stationary points:
- Find the first derivative, .
- Set and solve for .
- Substitute the values back into the original equation to find the corresponding values. This gives the coordinates of the stationary points.
There are two methods to determine the nature of stationary points:
Method 1: Second derivative test
- Find the second derivative, .
- Substitute the values of the stationary points into :
- If , the point is a minimum.
- If , the point is a maximum.
- If , the test is inconclusive. Use the first derivative test (Method 2).
Method 2: First derivative test (sign change of gradient)
- Consider the sign of the first derivative just before and just after the x-coordinate of the stationary point.
- If the sign changes from positive to negative, the point is a maximum.
- If the sign changes from negative to positive, the point is a minimum.
- If the sign does not change, the point is a point of inflexion.
Example 1
Identify the nature of the stationary points of .
Set : or .
When , . When , .
Stationary points: and .
When , . Thus, is a minimum point.
When , . The second derivative test is inconclusive. Use the first derivative test:
For (e.g., ), .
For (e.g., ), .
Since the gradient does not change sign, is a point of inflexion.
Example 2
A gardener has 400 m of fencing. Find the dimensions of a rectangular field to maximize the area.
Let be the length and be the width. The perimeter is , so .
Area:
Set : .
Then .
, so this is a maximum.
Dimensions: 100 m by 100 m. Maximum area: m².
Example 3
Find and classify the turning points of .
Set :
When ,
When ,
Turning points: and
When , . Minimum point.
When , . Maximum point.
Example 4
Find and classify the nature of the turning points for the function .
1. Find the first derivative
The first derivative, which represents the gradient of the curve, is:
2. Find the stationary points
Stationary points occur where the gradient is zero, so we set :
Divide by 4 to simplify:
By inspection (trying small integer values), we find that is a root:
Therefore, is a factor. We can perform polynomial division or factor by grouping to find the other factors:
The quadratic factor can be further factored:
This gives us two solutions for : and .
Now, we find the corresponding values:
- When : . So, one stationary point is .
- When : . So, the other stationary point is .
3. Classify the stationary points
We'll use the second derivative test first, and if it's inconclusive, we'll use the first derivative test.
Second derivative
The second derivative is:
Applying the second derivative test
- At : . Since the second derivative is positive, is a minimum point.
- At : . Since the second derivative is zero, the second derivative test is inconclusive.
Applying the first derivative test (for x = 2)
Since the second derivative test was inconclusive at , we examine the sign of the first derivative around :
- For slightly less than 2 (e.g., ): (Positive gradient)
- For slightly greater than 2 (e.g., ): (Positive gradient)
Since the gradient does not change sign around , the point is a point of inflexion.
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