Absolute and Local Extrema Definition (Absolute Maximum) A function - - PowerPoint PPT Presentation

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Absolute and Local Extrema Definition (Absolute Maximum) A function - - PowerPoint PPT Presentation

Absolute and Local Extrema Definition (Absolute Maximum) A function f has an absolute maximum at c S if f ( x ) f ( c ) x S . We call f ( c ) the absolute maximum of f on S . Alan H. SteinUniversity of Connecticut Absolute and


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SLIDE 1

Absolute and Local Extrema

Definition (Absolute Maximum)

A function f has an absolute maximum at c ∈ S if f (x) ≤ f (c) ∀x ∈ S. We call f (c) the absolute maximum of f on S.

Alan H. SteinUniversity of Connecticut

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SLIDE 2

Absolute and Local Extrema

Definition (Absolute Maximum)

A function f has an absolute maximum at c ∈ S if f (x) ≤ f (c) ∀x ∈ S. We call f (c) the absolute maximum of f on S.

Definition (Local Maximum)

A function f has a local maximum at c if f (x) ≤ f (c) ∀x in some

  • pen interval containing c. We call f (c) a local maximum of f .

Alan H. SteinUniversity of Connecticut

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SLIDE 3

Absolute and Local Extrema

Definition (Absolute Maximum)

A function f has an absolute maximum at c ∈ S if f (x) ≤ f (c) ∀x ∈ S. We call f (c) the absolute maximum of f on S.

Definition (Local Maximum)

A function f has a local maximum at c if f (x) ≤ f (c) ∀x in some

  • pen interval containing c. We call f (c) a local maximum of f .

Definition (Absolute Minimum)

A function f has an absolute minimum at c ∈ S if f (x) ≥ f (c) ∀x ∈ S. We call f (c) the absolute minimum of f on S.

Alan H. SteinUniversity of Connecticut

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SLIDE 4

Absolute and Local Extrema

Definition (Absolute Maximum)

A function f has an absolute maximum at c ∈ S if f (x) ≤ f (c) ∀x ∈ S. We call f (c) the absolute maximum of f on S.

Definition (Local Maximum)

A function f has a local maximum at c if f (x) ≤ f (c) ∀x in some

  • pen interval containing c. We call f (c) a local maximum of f .

Definition (Absolute Minimum)

A function f has an absolute minimum at c ∈ S if f (x) ≥ f (c) ∀x ∈ S. We call f (c) the absolute minimum of f on S.

Definition (Local Minimum)

A function f has a local minimum at c if f (x) ≥ f (c) ∀x in some

  • pen interval containing c. We call f (c) a local minimum of f .

Alan H. SteinUniversity of Connecticut

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SLIDE 5

Critical Points

In the proof of Rolle’s Theorem, we actually demonstrated the following theorem.

Alan H. SteinUniversity of Connecticut

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SLIDE 6

Critical Points

In the proof of Rolle’s Theorem, we actually demonstrated the following theorem.

Theorem

If f has a local extremum at a point c and f ′(c) exists, then f ′(c) = 0.

Alan H. SteinUniversity of Connecticut

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SLIDE 7

Critical Points

In the proof of Rolle’s Theorem, we actually demonstrated the following theorem.

Theorem

If f has a local extremum at a point c and f ′(c) exists, then f ′(c) = 0. This leads to the following definition and theorem.

Alan H. SteinUniversity of Connecticut

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SLIDE 8

Critical Points

In the proof of Rolle’s Theorem, we actually demonstrated the following theorem.

Theorem

If f has a local extremum at a point c and f ′(c) exists, then f ′(c) = 0. This leads to the following definition and theorem.

Definition (Critical Number)

A number c in the domain of a function f is called a critical number of f if either f ′(c) = 0 or f ′(c) is undefined.

Alan H. SteinUniversity of Connecticut

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SLIDE 9

Fermat’s Theorem

Theorem (Fermat’s Theorem)

Suppose f has a local extremum at c. Then c must be a critical number of f .

Alan H. SteinUniversity of Connecticut

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SLIDE 10

Fermat’s Theorem

Theorem (Fermat’s Theorem)

Suppose f has a local extremum at c. Then c must be a critical number of f . Thus, to find extrema of a function, we calculate the derivative and find where it equals 0 and where it doesn’t exist.

Alan H. SteinUniversity of Connecticut

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SLIDE 11

Monotonicity - Increasing and Decreasing

If a function is increasing on an interval, or if it is decreasing on an interval, we say it is monotonic.

Alan H. SteinUniversity of Connecticut

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SLIDE 12

Monotonicity - Increasing and Decreasing

If a function is increasing on an interval, or if it is decreasing on an interval, we say it is monotonic. When we wish to determine where a function is increasing and where it is decreasing, we say we wish to determine its monotonicity.

Alan H. SteinUniversity of Connecticut

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SLIDE 13

Monotonicity - Increasing and Decreasing

If a function is increasing on an interval, or if it is decreasing on an interval, we say it is monotonic. When we wish to determine where a function is increasing and where it is decreasing, we say we wish to determine its monotonicity. We have previously shown, using the Mean Value Theorem, that the derivative measures rate of change in the sense that if the derivative is positive then the function is increasing and if the derivative is negative then the function is decreasing.

Alan H. SteinUniversity of Connecticut

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SLIDE 14

Curve Sketching

Simply analyzing monotonicity and finding possible critical points is often enough to get a rough idea of what a graph looks like. We will soon round out the picture by looking at some additional factors.

Alan H. SteinUniversity of Connecticut

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SLIDE 15

Analysis of Extrema

We can combine Fermat’s Theorem and an analysis of monotonicity to determine the nature of local extema.

Alan H. SteinUniversity of Connecticut

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SLIDE 16

Analysis of Extrema

We can combine Fermat’s Theorem and an analysis of monotonicity to determine the nature of local extema. For example, if a continuous function has a critical point and is increasing to the left and decreasing to the right, it obviously must have a local maximum at the critical point. A similar argument deals with minima, leading to the following test.

Alan H. SteinUniversity of Connecticut

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SLIDE 17

First Derivative Test for Extrema

Theorem (First Derivative Test for Extrema)

Suppose that f is continuous on an open interval I containing a point c.

  • i. If f ′(x) > 0 for x ∈ I, x < c and f ′(x) < 0 for x ∈ I, x > c,

then f has a local maximum at c.

  • ii. If f ′(x) < 0 for x ∈ I, x < c and f ′(x) > 0 for x ∈ I, x > c,

then f has a local minimum at c.

Alan H. SteinUniversity of Connecticut

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SLIDE 18

First Derivative Test for Extrema

Theorem (First Derivative Test for Extrema)

Suppose that f is continuous on an open interval I containing a point c.

  • i. If f ′(x) > 0 for x ∈ I, x < c and f ′(x) < 0 for x ∈ I, x > c,

then f has a local maximum at c.

  • ii. If f ′(x) < 0 for x ∈ I, x < c and f ′(x) > 0 for x ∈ I, x > c,

then f has a local minimum at c. Note: This is not really something to memorize. Simply visualize whether the function is increasing or decreasing on either side of a critical point.

Alan H. SteinUniversity of Connecticut

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SLIDE 19

Concavity

We say a curve is concave up if the slope of its tangent increases as we go left to right and say it is concave down if the slope of its tangent decreases as we go left to right.

Alan H. SteinUniversity of Connecticut

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SLIDE 20

Concavity

We say a curve is concave up if the slope of its tangent increases as we go left to right and say it is concave down if the slope of its tangent decreases as we go left to right. Since the derivative measures rate of change, this immediately leads to the following theorem enabling us to use the derivative of the derivative, known as the second derivative, to analyze concavity.

Alan H. SteinUniversity of Connecticut

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SLIDE 21

Concavity

We say a curve is concave up if the slope of its tangent increases as we go left to right and say it is concave down if the slope of its tangent decreases as we go left to right. Since the derivative measures rate of change, this immediately leads to the following theorem enabling us to use the derivative of the derivative, known as the second derivative, to analyze concavity.

Theorem (Concavity)

If f ′′(x) > 0 for all x in some interval, then the graph of f is concave up on that interval. If f ′′(x) < 0 for all x in some interval, then the graph of f is concave down on that interval.

Alan H. SteinUniversity of Connecticut

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SLIDE 22

Concavity

We say a curve is concave up if the slope of its tangent increases as we go left to right and say it is concave down if the slope of its tangent decreases as we go left to right. Since the derivative measures rate of change, this immediately leads to the following theorem enabling us to use the derivative of the derivative, known as the second derivative, to analyze concavity.

Theorem (Concavity)

If f ′′(x) > 0 for all x in some interval, then the graph of f is concave up on that interval. If f ′′(x) < 0 for all x in some interval, then the graph of f is concave down on that interval. A graph is generally concave up near a minimum and concave down near a maximum. Knowing where a graph is concave down and where it is concave up further helps us to sketch a graph.

Alan H. SteinUniversity of Connecticut

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SLIDE 23

Summary So Far

We can often sketch a graph through the following steps suggested by the analysis so far of monotonicity and concavity.

Alan H. SteinUniversity of Connecticut

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SLIDE 24

Summary So Far

We can often sketch a graph through the following steps suggested by the analysis so far of monotonicity and concavity.

  • 1. Calculate f ′(x) and f ′′(x).

Alan H. SteinUniversity of Connecticut

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SLIDE 25

Summary So Far

We can often sketch a graph through the following steps suggested by the analysis so far of monotonicity and concavity.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.

Alan H. SteinUniversity of Connecticut

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SLIDE 26

Summary So Far

We can often sketch a graph through the following steps suggested by the analysis so far of monotonicity and concavity.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .

Alan H. SteinUniversity of Connecticut

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SLIDE 27

Summary So Far

We can often sketch a graph through the following steps suggested by the analysis so far of monotonicity and concavity.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .
  • 4. Analyze monotonicity.

Alan H. SteinUniversity of Connecticut

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SLIDE 28

Summary So Far

We can often sketch a graph through the following steps suggested by the analysis so far of monotonicity and concavity.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .
  • 4. Analyze monotonicity.
  • 5. Find the possible points of inflection by determining where

f ′′(x) = 0 or f ′′(x) doesn’t exist.

Alan H. SteinUniversity of Connecticut

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SLIDE 29

Summary So Far

We can often sketch a graph through the following steps suggested by the analysis so far of monotonicity and concavity.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .
  • 4. Analyze monotonicity.
  • 5. Find the possible points of inflection by determining where

f ′′(x) = 0 or f ′′(x) doesn’t exist.

  • 6. Analyze concavity.

Alan H. SteinUniversity of Connecticut

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SLIDE 30

Summary So Far

We can often sketch a graph through the following steps suggested by the analysis so far of monotonicity and concavity.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .
  • 4. Analyze monotonicity.
  • 5. Find the possible points of inflection by determining where

f ′′(x) = 0 or f ′′(x) doesn’t exist.

  • 6. Analyze concavity.
  • 7. Plot the critical points and possible points of inflection.

Alan H. SteinUniversity of Connecticut

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SLIDE 31

Summary So Far

We can often sketch a graph through the following steps suggested by the analysis so far of monotonicity and concavity.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .
  • 4. Analyze monotonicity.
  • 5. Find the possible points of inflection by determining where

f ′′(x) = 0 or f ′′(x) doesn’t exist.

  • 6. Analyze concavity.
  • 7. Plot the critical points and possible points of inflection.
  • 8. Connect those points appropriately using the information

about monotonicity and concavity.

Alan H. SteinUniversity of Connecticut

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SLIDE 32

Other Things To Consider

Often, an examination of monotonicity and concavity will give enough information to sketch a graph. Sometimes, it is useful to look at other properties such as intercepts, symmetry and

  • asymptotes. These are described below. As you gain experience

sketching graphs, you will begin to get a feeling for when it is worthwhile to give these properties more than a cursory consideration.

Alan H. SteinUniversity of Connecticut

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SLIDE 33

Intercepts

A point where a curve crosses one of the axes is called an intercept. There are two types of intercepts, x−intercepts and y−intercepts.

Alan H. SteinUniversity of Connecticut

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SLIDE 34

Intercepts

A point where a curve crosses one of the axes is called an intercept. There are two types of intercepts, x−intercepts and y−intercepts. Since a curve crosses the y−axis at a point where the first coordinate equals 0, you can calculate the y−intercept by simply evaluating f (0). This is usually fairly easy to calculate.

Alan H. SteinUniversity of Connecticut

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SLIDE 35

Intercepts

A point where a curve crosses one of the axes is called an intercept. There are two types of intercepts, x−intercepts and y−intercepts. Since a curve crosses the y−axis at a point where the first coordinate equals 0, you can calculate the y−intercept by simply evaluating f (0). This is usually fairly easy to calculate. Since a curve crosses the x−axis at a point where the second coordinate equals 0, you can calculate the x−intercept by solving the equation f (x) = 0. Depending on the formula for f , this may be very difficult to solve and often is not worth the effort.

Alan H. SteinUniversity of Connecticut

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SLIDE 36

Intercepts

A point where a curve crosses one of the axes is called an intercept. There are two types of intercepts, x−intercepts and y−intercepts. Since a curve crosses the y−axis at a point where the first coordinate equals 0, you can calculate the y−intercept by simply evaluating f (0). This is usually fairly easy to calculate. Since a curve crosses the x−axis at a point where the second coordinate equals 0, you can calculate the x−intercept by solving the equation f (x) = 0. Depending on the formula for f , this may be very difficult to solve and often is not worth the effort. It’s generally important to find the y−intercept when it’s unclear whether the curve crosses the y−axis above or below the origin, since drawing a picture with the curve crossing the y−axis on the wrong side of the origin presents a misleading picture.

Alan H. SteinUniversity of Connecticut

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SLIDE 37

Intercepts

A point where a curve crosses one of the axes is called an intercept. There are two types of intercepts, x−intercepts and y−intercepts. Since a curve crosses the y−axis at a point where the first coordinate equals 0, you can calculate the y−intercept by simply evaluating f (0). This is usually fairly easy to calculate. Since a curve crosses the x−axis at a point where the second coordinate equals 0, you can calculate the x−intercept by solving the equation f (x) = 0. Depending on the formula for f , this may be very difficult to solve and often is not worth the effort. It’s generally important to find the y−intercept when it’s unclear whether the curve crosses the y−axis above or below the origin, since drawing a picture with the curve crossing the y−axis on the wrong side of the origin presents a misleading picture. It’s important to find the x−intercepts when you’re not sure whether or not the curve crosses the x−axis.

Alan H. SteinUniversity of Connecticut

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SLIDE 38

Symmetry

There are two types of symmetry that are sometimes worth paying attention to, symmetry about the y−axis and symmetry about the

  • rigin.

Alan H. SteinUniversity of Connecticut

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SLIDE 39

Symmetry

There are two types of symmetry that are sometimes worth paying attention to, symmetry about the y−axis and symmetry about the

  • rigin.

Even functions are symmetric about the y−axis. You can check whether a function is even by seeing if f (−x) = f (x) for all values

  • f x. Polynomial functions that contain only even powers, such as

f (x) = x8 − 5x2 + 3, are examples of even functions. The cosine function is also an example of an even function.

Alan H. SteinUniversity of Connecticut

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SLIDE 40

Symmetry

There are two types of symmetry that are sometimes worth paying attention to, symmetry about the y−axis and symmetry about the

  • rigin.

Even functions are symmetric about the y−axis. You can check whether a function is even by seeing if f (−x) = f (x) for all values

  • f x. Polynomial functions that contain only even powers, such as

f (x) = x8 − 5x2 + 3, are examples of even functions. The cosine function is also an example of an even function. Odd functions are symmetric about the origin. You can check whether a function is odd by seeing if f (−x) = −f (x) for all values

  • f x. Polynomial functions that contain only odd powers, such as

f (x) = 10x7 + 8x3 − x, are examples of odd functions. The sine function is also an example of an odd function.

Alan H. SteinUniversity of Connecticut

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SLIDE 41

When to Check Symmetry

It is never actually absolutely necessary to check for symmetry. However, if you recognize from the formula for a function that its graph should exhibit symmetry, then you have another check for whether you have sketched the graph correctly.

Alan H. SteinUniversity of Connecticut

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SLIDE 42

Asymptotes

There are two types of asymptotes, horizontal and vertical.

Alan H. SteinUniversity of Connecticut

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SLIDE 43

Asymptotes

There are two types of asymptotes, horizontal and vertical. A graph will have a horizontal asymptote y = α if limx→∞ f (x) = α. In that case, the right side of the curve will get closer and closer to the horizontal asymptote, the line y = α. For example, if f (x) = (10x + 3)/(2x − 1), then limx→∞ f (x) = 5, so that the line y = 5 is a horizontal asymptote.

Alan H. SteinUniversity of Connecticut

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SLIDE 44

Asymptotes

There are two types of asymptotes, horizontal and vertical. A graph will have a horizontal asymptote y = α if limx→∞ f (x) = α. In that case, the right side of the curve will get closer and closer to the horizontal asymptote, the line y = α. For example, if f (x) = (10x + 3)/(2x − 1), then limx→∞ f (x) = 5, so that the line y = 5 is a horizontal asymptote. Similarly, a graph will have a horizontal asymptote y = α if limx→−∞ f (x) = α. In that case, the left side of the curve will get closer and closer to the horizontal asymptote, the line y = α. For example, if f (x) = (15x + 3)/(5x − 1), then limx→−∞ f (x) = 3, so that the line y = 3 is a horizontal asymptote.

Alan H. SteinUniversity of Connecticut

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SLIDE 45

When to Check

It’s worth checking for a horizontal asymptote on the right hand side if, for large x, either f is increasing and concave down or decreasing and concave up. (Clearly, there can be no such asymptote if f is increasing and concave up or decreasing and concave down. Draw a picture to see why.)

Alan H. SteinUniversity of Connecticut

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SLIDE 46

Vertical Asymptotes

A graph will have a vertical asymptote x = α if either limx→α+ f (x) = ∞, limx→α+ f (x) = −∞, limx→α− f (x) = ∞ or limx→α− f (x) = −∞. For example, if limx→α+ = ∞, it follows that if a point (x, y) is on the graph and x is just a little bigger than α, then y must be very large and hence the curve must be close to the line x = α. Similar arguments hold for each of the other cases.

Alan H. SteinUniversity of Connecticut

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SLIDE 47

Vertical Asymptotes

A graph will have a vertical asymptote x = α if either limx→α+ f (x) = ∞, limx→α+ f (x) = −∞, limx→α− f (x) = ∞ or limx→α− f (x) = −∞. For example, if limx→α+ = ∞, it follows that if a point (x, y) is on the graph and x is just a little bigger than α, then y must be very large and hence the curve must be close to the line x = α. Similar arguments hold for each of the other cases. Since vertical asymptotes, by their very nature, can exist only at discontinuities, it is generally a simple matter to recognize possible

  • asymptotes. You can look for some of the the same clues that lead

you to look for discontinuities—denominators that are zero. Once you suspect that x = α is a vertical asymptote, check the two

  • ne-sided limits at α.

Alan H. SteinUniversity of Connecticut

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SLIDE 48

Example

For example, let f (x) = x/(x − 3)2. Clearly, the denominator is zero when x = 3, so x = 3 is a possible vertical asymptote. Since limx→3+ x/(x − 3)2 = ∞, the line x = 3 is a vertical asymptote for the portion of the curve on the right. Since limx→3− x/(x − 3)2 = ∞ also, the line x = 3 is also vertical asymptote for the portion of the curve on the left.

Alan H. SteinUniversity of Connecticut

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SLIDE 49

Summary of Curve Sketching

Putting everything together, we have the following steps.

Alan H. SteinUniversity of Connecticut

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SLIDE 50

Summary of Curve Sketching

Putting everything together, we have the following steps.

  • 1. Calculate f ′(x) and f ′′(x).

Alan H. SteinUniversity of Connecticut

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SLIDE 51

Summary of Curve Sketching

Putting everything together, we have the following steps.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.

Alan H. SteinUniversity of Connecticut

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SLIDE 52

Summary of Curve Sketching

Putting everything together, we have the following steps.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .

Alan H. SteinUniversity of Connecticut

slide-53
SLIDE 53

Summary of Curve Sketching

Putting everything together, we have the following steps.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .
  • 4. Analyze monotonicity.

Alan H. SteinUniversity of Connecticut

slide-54
SLIDE 54

Summary of Curve Sketching

Putting everything together, we have the following steps.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .
  • 4. Analyze monotonicity.
  • 5. Find the possible points of inflection by determining where

f ′′(x) = 0 or f ′′(x) doesn’t exist.

Alan H. SteinUniversity of Connecticut

slide-55
SLIDE 55

Summary of Curve Sketching

Putting everything together, we have the following steps.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .
  • 4. Analyze monotonicity.
  • 5. Find the possible points of inflection by determining where

f ′′(x) = 0 or f ′′(x) doesn’t exist.

  • 6. Analyze concavity.

Alan H. SteinUniversity of Connecticut

slide-56
SLIDE 56

Summary of Curve Sketching

Putting everything together, we have the following steps.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .
  • 4. Analyze monotonicity.
  • 5. Find the possible points of inflection by determining where

f ′′(x) = 0 or f ′′(x) doesn’t exist.

  • 6. Analyze concavity.
  • 7. Plot the critical points and possible points of inflection.

Alan H. SteinUniversity of Connecticut

slide-57
SLIDE 57

Summary of Curve Sketching

Putting everything together, we have the following steps.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .
  • 4. Analyze monotonicity.
  • 5. Find the possible points of inflection by determining where

f ′′(x) = 0 or f ′′(x) doesn’t exist.

  • 6. Analyze concavity.
  • 7. Plot the critical points and possible points of inflection.
  • 8. Connect those points appropriately using the information

about monotonicity and concavity.

Alan H. SteinUniversity of Connecticut

slide-58
SLIDE 58

Summary of Curve Sketching

Putting everything together, we have the following steps.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .
  • 4. Analyze monotonicity.
  • 5. Find the possible points of inflection by determining where

f ′′(x) = 0 or f ′′(x) doesn’t exist.

  • 6. Analyze concavity.
  • 7. Plot the critical points and possible points of inflection.
  • 8. Connect those points appropriately using the information

about monotonicity and concavity.

  • 9. Find intercepts if necessary.

Alan H. SteinUniversity of Connecticut

slide-59
SLIDE 59

Summary of Curve Sketching

Putting everything together, we have the following steps.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .
  • 4. Analyze monotonicity.
  • 5. Find the possible points of inflection by determining where

f ′′(x) = 0 or f ′′(x) doesn’t exist.

  • 6. Analyze concavity.
  • 7. Plot the critical points and possible points of inflection.
  • 8. Connect those points appropriately using the information

about monotonicity and concavity.

  • 9. Find intercepts if necessary.
  • 10. Check for symmetry if useful.

Alan H. SteinUniversity of Connecticut

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SLIDE 60

Summary of Curve Sketching

Putting everything together, we have the following steps.

  • 1. Calculate f ′(x) and f ′′(x).
  • 2. Factor f ′(x) and f ′′(x) completely.
  • 3. Find the critical points of f .
  • 4. Analyze monotonicity.
  • 5. Find the possible points of inflection by determining where

f ′′(x) = 0 or f ′′(x) doesn’t exist.

  • 6. Analyze concavity.
  • 7. Plot the critical points and possible points of inflection.
  • 8. Connect those points appropriately using the information

about monotonicity and concavity.

  • 9. Find intercepts if necessary.
  • 10. Check for symmetry if useful.
  • 11. Check for horizontal and vertical asymptotes if needed.

Alan H. SteinUniversity of Connecticut