Derivatives and the Product Rule

Size: px
Start display at page:

Download "Derivatives and the Product Rule"

Transcription

1 Derivatives and the Product Rule James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University January 28, 2014

2 Outline 1 Differentiability 2 Simple Derivatives 3 The Product Rule

3 This lecture will go over the details of derivatives and the product rule. Lots of new details and ideas, so pull up a chair and grab your favorite beverage.

4 Differentiability We have already discussed what a derivative means in our opening salvo on limits. I m sure you remember the pain and the agony. Still, we do need to get proper tools to build our models, so let s revisit this again but this time with a bit more detail.

5 Differentiability We have already discussed what a derivative means in our opening salvo on limits. I m sure you remember the pain and the agony. Still, we do need to get proper tools to build our models, so let s revisit this again but this time with a bit more detail. Differentiability is an idea we need to discuss more carefully. From what we have said before, it seems a formal definition of a derivative at a point would be this.

6 Differentiability Definition Differentiability of A Function At A Point: f is said to be differentiable at a point p in its domain if the f (t) f (p) t p limit as t approaches p, t p, of the quotients exists. When this limit exists, the value of this limit is denoted by a number of possible symbols: f (p) or df dt (p). This can also be phrased in terms of the right and left hand limits f (p + f (t) f (p) ) = lim t p + t p and f (p ) = lim t p If both exist and match at p, then f (p) exists and the value of the derivative is the common value. f (t) f (p) t p.

7 Differentiability All of our usual machinery about limits can be brought to bear here. For example, all of the limit stuff could be rephrased in the ɛ δ framework but we seldom need to go that deep.

8 Differentiability All of our usual machinery about limits can be brought to bear here. For example, all of the limit stuff could be rephrased in the ɛ δ framework but we seldom need to go that deep. However, the most useful way of all to view the derivative is to use an error term.

9 Differentiability All of our usual machinery about limits can be brought to bear here. For example, all of the limit stuff could be rephrased in the ɛ δ framework but we seldom need to go that deep. However, the most useful way of all to view the derivative is to use an error term. Let E(x p) = f (x) f (p) f (p) (x p).

10 Differentiability If the derivative exists, we can use the ɛ δ formlism to get some important information about the error. Choose ɛ = 1. Then by definition, there is a radius δ so that x p < δ = f (x) f (p) f (p) x p < 1.

11 Differentiability If the derivative exists, we can use the ɛ δ formlism to get some important information about the error. Choose ɛ = 1. Then by definition, there is a radius δ so that x p < δ = f (x) f (p) f (p) x p < 1. We can rewrite this by getting a common denominator as x p < δ = f (x) f (p) f (p)(x p) x p < 1.

12 Differentiability If the derivative exists, we can use the ɛ δ formlism to get some important information about the error. Choose ɛ = 1. Then by definition, there is a radius δ so that x p < δ = f (x) f (p) f (p) x p < 1. We can rewrite this by getting a common denominator as x p < δ = f (x) f (p) f (p)(x p) x p < 1. But the numerator here is the error, so we have x p < δ = E(x p) x p < 1.

13 Differentiability This tells us x p < δ = E(x p) < x p.

14 Differentiability This tells us x p < δ = E(x p) < x p. So as x p, x p 0 and the above tells us E(x p) 0 as well. Good to know as we will put this fact to use right away.

15 Differentiability Definition Error Form for Differentiability of A Function At A Point: Let the value of the derivative of f at p be denoted by f (p) and let the error term E(x p) be defined by E(x p) = f (x) f (p) f (p) (x p). Then if f (p) exists, the arguments above show us E(0) = 0 (i.e x = p and everything disappears). E(x p) 0 as x p and E(x p)/(x p) 0 as x p also. So the error acts like (x p) 2! Going the other way, if there is a number L so that E(x p) = f (x) f (p) L (x p) satisfies the same two conditions, then f has a derivative at p whose value is L. We say f has derivative f (p) if and only if the error E(x p) and E(x p)/(x p) goes to 0 as x p.

16 Differentiability Here is an example which should help. We will take our old friend f (x) = x 2. Let s look at the derivative of f at the point x. We have E( x) = f (x + x) f (x) f (x) x = (x + x) 2 x 2 2x x = 2x x + ( x) 2 2x x = ( x) 2.

17 Differentiability Here is an example which should help. We will take our old friend f (x) = x 2. Let s look at the derivative of f at the point x. We have E( x) = f (x + x) f (x) f (x) x = (x + x) 2 x 2 2x x = 2x x + ( x) 2 2x x = ( x) 2. See how E( x) = ( x) 2 0 and E( x)/ x = x 0 as x 0? This is the essential nature of the derivative.

18 Differentiability Here is an example which should help. We will take our old friend f (x) = x 2. Let s look at the derivative of f at the point x. We have E( x) = f (x + x) f (x) f (x) x = (x + x) 2 x 2 2x x = 2x x + ( x) 2 2x x = ( x) 2. See how E( x) = ( x) 2 0 and E( x)/ x = x 0 as x 0? This is the essential nature of the derivative. Replacing the original function value f (x + x) by the value given by the straight line f (x) + f (x) x makes an error that is roughly proportional to ( x) 2. Good to know.

19 Differentiability Also, note using the error definition, if we can find a number L so that E(x p) = f (x) f (p) L (x p) goes to zero in the two ways above, we know f (p) = L. This is a fabulous tool.

20 Differentiability Also, note using the error definition, if we can find a number L so that E(x p) = f (x) f (p) L (x p) goes to zero in the two ways above, we know f (p) = L. This is a fabulous tool. A fundamental consequence of the existence of a derivative of a function at a point t is that it must also be continuous there. This is easy to see using the error form of the derivative. If f has a derivative at p, we know that f (x) = f (p) + f (p) (x p) + E(x p)

21 Differentiability Also, note using the error definition, if we can find a number L so that E(x p) = f (x) f (p) L (x p) goes to zero in the two ways above, we know f (p) = L. This is a fabulous tool. A fundamental consequence of the existence of a derivative of a function at a point t is that it must also be continuous there. This is easy to see using the error form of the derivative. If f has a derivative at p, we know that f (x) = f (p) + f (p) (x p) + E(x p) as x p, we get lim x p f (x) = f (p) because the other terms vanish. So having a derivative implies continuity.

22 Differentiability Think of continuity as a first level of smoothness and having a derivative as the second level of smoothness. So things at the second level should get the first level for free! And they do. Theorem Differentiability Implies Continuity Let f be a function which is differentiable at a point t in its domain. Then f is also continuous at t. Proof We just did this argument!

23 Differentiability Example Example We can show the derivative of f (x) = x 3 is 3x 2. Using this, write down the definition of the derivative at x = 1 and also the error form at x = 1. State the two conditions on the error too. Solution The definition of the derivative is The error form is dy (1) = lim dx h 0 (1 + h) 3 (1) 3. h x 3 = (1) (1) 2 (x 1) + E(x 1) where E(x 1) and E(x 1)/(x 1) both go to zero as x 1.

24 Differentiability Example Example We can show the derivative of f (x) = sin(x) is cos(x). Using this, write down the definition of the derivative at x = 2 and also the error form at x = 2. State the two conditions on the error too. Solution The definition of the derivative is The error form is dy (2) = lim dx h 0 sin(2 + h) sin(2). h sin(x) = sin(2) + cos(2) (x 2) + E(x 2) where E(x 2) and E(x 2)/(x 2) both go to zero as x 2.

25 Differentiability Example Example We know f (x) = x 5 has a derivative at each x and equals 5x 4. Explain why f (x) = x 5 must be a continuous function. Solution x 5 is continuous since it has a derivative. Example Suppose a function has a jump at the point x = 5. Can this function have a derivative there? Solution No. If the function did have a derivative there, it would have to be continuous there which it is not since it has a jump at that point.

26 Differentiability Homework Suppose a function has a jump at the point x = 2. Can this function have a derivative there? 12.2 We know f (x) = cos(x) has a derivative at each x and equals sin(x). Explain why f (x) = cos(x) must be a continuous function We can show the derivative of f (x) = x 7 is 7x 6. Using this, write down the definition of the derivative at x = 1 and also the error form at x = 1. State the two conditions on the error too We can show the derivative of f (x) = x is 2x. Using this, write down the definition of the derivative at x = 4 and also the error form at x = 4. State the two conditions on the error too.

27 Simple Derivatives We need some fast ways to calculate these derivatives. Let s start with constant functions. These never change and since derivatives are supposed to give rates of change, we would expect this to be zero. Here is the argument.

28 Simple Derivatives We need some fast ways to calculate these derivatives. Let s start with constant functions. These never change and since derivatives are supposed to give rates of change, we would expect this to be zero. Here is the argument. Let f (x) = 5 for all x. Then to find the derivative at any x, we calculate this limit dy f (x + h) f (x) (x) = lim dx h 0 h 5 5 = lim h 0 h = lim 0 = 0. h 0

29 Simple Derivatives We need some fast ways to calculate these derivatives. Let s start with constant functions. These never change and since derivatives are supposed to give rates of change, we would expect this to be zero. Here is the argument. Let f (x) = 5 for all x. Then to find the derivative at any x, we calculate this limit dy f (x + h) f (x) (x) = lim dx h 0 h 5 5 = lim h 0 h = lim 0 = 0. h 0 A little thought shows that the value 5 doesn t matter. So we have a general result which we dignify by calling it a theorem just because we can!

30 Simple Derivatives Theorem The Derivative of a constant: If c is any number, then the function f (t) = c gives a constant function. The derivative of c with respect to t is then zero. Proof We just hammered this out!

31 Simple Derivatives Let s do one more, the derivative of f (x) = x. This one is easy too. We calculate dy (x) = lim dx h 0 f (x + h) f (x) h = lim h 0 x + h x h = lim h = lim 1 = 1. h 0 h 0 h

32 Simple Derivatives Let s do one more, the derivative of f (x) = x. This one is easy too. We calculate dy (x) = lim dx h 0 f (x + h) f (x) h = lim h 0 x + h x h = lim h = lim 1 = 1. h 0 h 0 h So now we know that d dx (x) = 1 and it wasn t that hard. To find the derivatives of more powers of x, we are going to find an easy way. The easy way is to prove a general rule and then apply it to the two examples we know. This general rule is called the Product Rule.

33 The Product Rule Theorem The Product Rule: If f and g are both differentiable at a point x, then the product fg is also differentiable at x and has the value ( f (x) g(x)) = f (x) g(x) + f (x) g (x) Proof We need to find this limit at the point x: d (fg)(x) = lim dx h 0 f (x + h) g(x + h) f (x) g(x). h

34 The Product Rule Proof Looks forbidding doesn t it? Let s add and subtract just the right term: d dx (fg)(x) = lim h 0 f (x + h)g(x + h) f (x) g(x + h) + f (x) g(x + h) f (x) g(x). h Now group the pieces like so: d dx (fg)(x) = ( ) f (x + h)g(x + h) f (x)g(x + h) lim h 0 h ( ) + f (x)g(x + h) f (x)g(x).

35 The Product Rule Proof Factor out common terms: d dx (fg)(x) = ( ) f (x + h) f (x) g(x + h) + lim h 0 h ( ) g(x + h) g(x) Now rewrite as two separate limits: ( ) d f (x + h) f (x) (fg)(x) = lim g(x + h) dx h 0 h ( ) g(x + h) g(x) + lim f (x) h 0 h f (x).

36 The Product Rule Proof Almost there. In the first limit, the first part goes to f (x) and the second part goes to g(x) because since g has a derivative at x, g is continuous at x. In the second limit, the f (x) doesn t change and the other piece goes to g (x). So there you have it: d dx (f (x) g(x)) = f (x) g(x) + f (x) g (x).

37 The Product Rule We are now ready to blow your mind as Jack Black would say. Let f (x) = x 2. Let s apply the product rule. The first function is x and the second one is x also. d dx (x 2 ) = d dx (x) x + (x) d dx (x) = (1) (x) + (x) (1) = 2 x. This is just what we had before!

38 The Product Rule We are now ready to blow your mind as Jack Black would say. Let f (x) = x 2. Let s apply the product rule. The first function is x and the second one is x also. d dx (x 2 ) = d dx (x) x + (x) d dx (x) = (1) (x) + (x) (1) = 2 x. This is just what we had before! Let f (x) = x 3. Let s apply the product rule here. The first function is x 2 and the second one is x. d dx (x 3 ) = d dx (x 2 ) x + (x 2 ) d dx (x) = (2 x) (x) + (x 2 ) (1) = 3 x 2.

39 The Product Rule We are now ready to blow your mind as Jack Black would say. Let f (x) = x 2. Let s apply the product rule. The first function is x and the second one is x also. d dx (x 2 ) = d dx (x) x + (x) d dx (x) = (1) (x) + (x) (1) = 2 x. This is just what we had before! Let f (x) = x 3. Let s apply the product rule here. The first function is x 2 and the second one is x. d dx (x 3 ) = d dx (x 2 ) x + (x 2 ) d dx (x) = (2 x) (x) + (x 2 ) (1) = 3 x 2. Let f (x) = x 4. Let s apply the product rule again. The first function is x 3 and the second one is x. d dx (x 4 ) = d dx (x 3 ) x + (x 3 ) d dx (x) = (3 x 2 ) (x) + (x 3 ) (1) = 4 x 3.

40 The Product Rule We could go on, but you probably see the pattern. If P is a positive integer, then d dx x P = P x P 1. That s all there is too it. Just to annoy you, we ll state it as a Theorem: Theorem The Simple Power Rule: Positive Integers: If f is the function x P for any positive integer P, then the derivative of f with respect to x satisfies (x P) = P x P 1 Proof We just reasoned this out!

41 The Product Rule Next, we don t want to overload you with a lot of tedious proofs of various properties, so let s just get to the chase. From the way the derivative is defined as a limit, it is pretty clear the following properties hold: first the derivative of a sum of functions is the sum of the derivatives:

42 The Product Rule Next, we don t want to overload you with a lot of tedious proofs of various properties, so let s just get to the chase. From the way the derivative is defined as a limit, it is pretty clear the following properties hold: first the derivative of a sum of functions is the sum of the derivatives: Second, the derivative of a constant times a function is just constant times the derivative. d dx (c f (x)) = c d (f (x)). dx Armed with these tools, we can take a lot of derivatives!

43 The Product Rule Example Polynomials: Example Find ( t ). Solution ( t 2 + 4) ) = 2t.

44 The Product Rule Example Polynomials: Example Find ( 3 t ). Solution ( 3 t ) = 12 t 3.

45 The Product Rule Example Example Find ( 3 t t 5 2 t ). Solution ( 3 t t 5 2 t ) = 24 t t 4 4 t.

46 The Product Rule Example Product Rules: Example Find ( (t 2 + 4) (5t 3 + t 2 4) ). Solution ( (t 2 + 4) (5t 3 + t 2 4) ) = (2t) (5t 3 + t 2 4) + (t 2 + 4) (15t 2 + 2t) and, of course, this expression above can be further simplified.

47 The Product Rule Example Example Find ( (2t 3 + t + 5) ( 2t 6 + t ) ). Solution ( (2t 3 + t + 5) ( 2t 6 + t ) ) = (6t 2 + 1) ( 2t 6 + t ) + (2t 3 + t + 5) ( 12t 5 + 3t 2 )

48 The Product Rule Homework Find ( 6 t t 2) Find ( 3 t t + 11 ) Find ( 2 t t 2 2 t + 1 ) Find ( t + 7 t 10) Find ( 3 t + 7 t 8).

49 The Product Rule Homework Find ( (6t + 4) (4t 2 + t) ) Find ( (5t 4 + t ) (4 t + t 2 + 3) ) Find ( ( 8t 3 + t 4 ) (4 t + t 8 ) ) Find ( ( 10t t 5 + 8t 2 + 8) (5t 2 + t 9 ) ) Find ( (8t 11 + t 15 ) ( 5t 2 + 8t 2) ).

Derivatives and the Product Rule

Derivatives and the Product Rule Derivatives an the Prouct Rule James K. Peterson Department of Biological Sciences an Department of Mathematical Sciences Clemson University January 28, 2014 Outline Differentiability Simple Derivatives

More information

Sin, Cos and All That

Sin, Cos and All That Sin, Cos and All That James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University March 9, 2017 Outline 1 Sin, Cos and all that! 2 A New Power Rule 3

More information

The First Derivative and Second Derivative Test

The First Derivative and Second Derivative Test The First Derivative and Second Derivative Test James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University April 9, 2018 Outline 1 Extremal Values 2

More information

Sin, Cos and All That

Sin, Cos and All That Sin, Cos and All That James K Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University September 9, 2014 Outline Sin, Cos and all that! A New Power Rule Derivatives

More information

The First Derivative and Second Derivative Test

The First Derivative and Second Derivative Test The First Derivative and Second Derivative Test James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University November 8, 2017 Outline Extremal Values The

More information

Antiderivatives! Outline. James K. Peterson. January 28, Antiderivatives. Simple Fractional Power Antiderivatives

Antiderivatives! Outline. James K. Peterson. January 28, Antiderivatives. Simple Fractional Power Antiderivatives Antiderivatives! James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University January 28, 2014 Outline Antiderivatives Simple Fractional Power Antiderivatives

More information

Fourier Sin and Cos Series and Least Squares Convergence

Fourier Sin and Cos Series and Least Squares Convergence Fourier and east Squares Convergence James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University May 7, 28 Outline et s look at the original Fourier sin

More information

Antiderivatives! James K. Peterson. January 28, Department of Biological Sciences and Department of Mathematical Sciences Clemson University

Antiderivatives! James K. Peterson. January 28, Department of Biological Sciences and Department of Mathematical Sciences Clemson University ! James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University January 28, 2014 Outline 1 2 Simple Fractional Power Abstract This lecture is going to talk

More information

The Derivative of a Function

The Derivative of a Function The Derivative of a Function James K Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University March 1, 2017 Outline A Basic Evolutionary Model The Next Generation

More information

Geometric Series and the Ratio and Root Test

Geometric Series and the Ratio and Root Test Geometric Series and the Ratio and Root Test James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University September 5, 2018 Outline 1 Geometric Series

More information

Dirchlet s Function and Limit and Continuity Arguments

Dirchlet s Function and Limit and Continuity Arguments Dirchlet s Function and Limit and Continuity Arguments James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University February 23, 2018 Outline 1 Dirichlet

More information

Predator - Prey Model Trajectories and the nonlinear conservation law

Predator - Prey Model Trajectories and the nonlinear conservation law Predator - Prey Model Trajectories and the nonlinear conservation law James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University October 28, 2013 Outline

More information

Derivatives: definition and computation

Derivatives: definition and computation Math 10A September 6, 2016 Announcements The breakfasts tomorrow and Thursday are full, but there are spaces at the 8AM breakfast on September 13. This is a breakfast from last semester. The gentleman

More information

DIFFERENTIATION AND INTEGRATION PART 1. Mr C s IB Standard Notes

DIFFERENTIATION AND INTEGRATION PART 1. Mr C s IB Standard Notes DIFFERENTIATION AND INTEGRATION PART 1 Mr C s IB Standard Notes In this PDF you can find the following: 1. Notation 2. Keywords Make sure you read through everything and the try examples for yourself before

More information

Riemann Sums. Outline. James K. Peterson. September 15, Riemann Sums. Riemann Sums In MatLab

Riemann Sums. Outline. James K. Peterson. September 15, Riemann Sums. Riemann Sums In MatLab Riemann Sums James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University September 15, 2013 Outline Riemann Sums Riemann Sums In MatLab Abstract This

More information

ter. on Can we get a still better result? Yes, by making the rectangles still smaller. As we make the rectangles smaller and smaller, the

ter. on Can we get a still better result? Yes, by making the rectangles still smaller. As we make the rectangles smaller and smaller, the Area and Tangent Problem Calculus is motivated by two main problems. The first is the area problem. It is a well known result that the area of a rectangle with length l and width w is given by A = wl.

More information

Mathematical Induction

Mathematical Induction Mathematical Induction James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University January 12, 2017 Outline Introduction to the Class Mathematical Induction

More information

Geometric Series and the Ratio and Root Test

Geometric Series and the Ratio and Root Test Geometric Series and the Ratio and Root Test James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University September 5, 2017 Outline Geometric Series The

More information

Taylor Polynomials. James K. Peterson. Department of Biological Sciences and Department of Mathematical Sciences Clemson University

Taylor Polynomials. James K. Peterson. Department of Biological Sciences and Department of Mathematical Sciences Clemson University James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University September 24, 2013 Outline 1 First Order Approximation s Second Order Approximations 2 Approximation

More information

Convergence of Sequences

Convergence of Sequences James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University September 5, 2018 Outline 1 2 Homework Definition Let (a n ) n k be a sequence of real numbers.

More information

Tangent Lines Sec. 2.1, 2.7, & 2.8 (continued)

Tangent Lines Sec. 2.1, 2.7, & 2.8 (continued) Tangent Lines Sec. 2.1, 2.7, & 2.8 (continued) Prove this Result How Can a Derivative Not Exist? Remember that the derivative at a point (or slope of a tangent line) is a LIMIT, so it doesn t exist whenever

More information

More On Exponential Functions, Inverse Functions and Derivative Consequences

More On Exponential Functions, Inverse Functions and Derivative Consequences More On Exponential Functions, Inverse Functions and Derivative Consequences James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University January 10, 2019

More information

Chapter 5: Integrals

Chapter 5: Integrals Chapter 5: Integrals Section 5.3 The Fundamental Theorem of Calculus Sec. 5.3: The Fundamental Theorem of Calculus Fundamental Theorem of Calculus: Sec. 5.3: The Fundamental Theorem of Calculus Fundamental

More information

Hölder s and Minkowski s Inequality

Hölder s and Minkowski s Inequality Hölder s and Minkowski s Inequality James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University September 1, 218 Outline Conjugate Exponents Hölder s

More information

Sin, Cos and All That

Sin, Cos and All That Sin, Cos and All Tat James K. Peterson Department of Biological Sciences and Department of Matematical Sciences Clemson University Marc 9, 2017 Outline Sin, Cos and all tat! A New Power Rule Derivatives

More information

Dirchlet s Function and Limit and Continuity Arguments

Dirchlet s Function and Limit and Continuity Arguments Dirchlet s Function and Limit and Continuity Arguments James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University November 2, 2018 Outline Dirichlet

More information

CHAPTER 7: TECHNIQUES OF INTEGRATION

CHAPTER 7: TECHNIQUES OF INTEGRATION CHAPTER 7: TECHNIQUES OF INTEGRATION DAVID GLICKENSTEIN. Introduction This semester we will be looking deep into the recesses of calculus. Some of the main topics will be: Integration: we will learn how

More information

Convergence of Fourier Series

Convergence of Fourier Series MATH 454: Analysis Two James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University April, 8 MATH 454: Analysis Two Outline The Cos Family MATH 454: Analysis

More information

Math101, Sections 2 and 3, Spring 2008 Review Sheet for Exam #2:

Math101, Sections 2 and 3, Spring 2008 Review Sheet for Exam #2: Math101, Sections 2 and 3, Spring 2008 Review Sheet for Exam #2: 03 17 08 3 All about lines 3.1 The Rectangular Coordinate System Know how to plot points in the rectangular coordinate system. Know the

More information

Convergence of Sequences

Convergence of Sequences Convergence of Sequences James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University February 12, 2018 Outline Convergence of Sequences Definition Let

More information

11.5. The Chain Rule. Introduction. Prerequisites. Learning Outcomes

11.5. The Chain Rule. Introduction. Prerequisites. Learning Outcomes The Chain Rule 11.5 Introduction In this Section we will see how to obtain the derivative of a composite function (often referred to as a function of a function ). To do this we use the chain rule. This

More information

Section 1.x: The Variety of Asymptotic Experiences

Section 1.x: The Variety of Asymptotic Experiences calculus sin frontera Section.x: The Variety of Asymptotic Experiences We talked in class about the function y = /x when x is large. Whether you do it with a table x-value y = /x 0 0. 00.0 000.00 or with

More information

Math 111: Calculus. David Perkinson

Math 111: Calculus. David Perkinson Math : Calculus David Perkinson Fall 207 Contents Week, Monday: Introduction: derivatives, integrals, and the fundamental theorem. 5 Week, Wednesday: Average speed, instantaneous speed. Definition of the

More information

Mathematical Economics: Lecture 2

Mathematical Economics: Lecture 2 Mathematical Economics: Lecture 2 Yu Ren WISE, Xiamen University September 25, 2012 Outline 1 Number Line The number line, origin (Figure 2.1 Page 11) Number Line Interval (a, b) = {x R 1 : a < x < b}

More information

Cable Convergence. James K. Peterson. May 7, Department of Biological Sciences and Department of Mathematical Sciences Clemson University

Cable Convergence. James K. Peterson. May 7, Department of Biological Sciences and Department of Mathematical Sciences Clemson University Cable Convergence James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University May 7, 2018 Outline 1 Fourier Series Convergence Redux 2 Fourier Series

More information

Differentiating Series of Functions

Differentiating Series of Functions Differentiating Series of Functions James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University October 30, 017 Outline 1 Differentiating Series Differentiating

More information

2t t dt.. So the distance is (t2 +6) 3/2

2t t dt.. So the distance is (t2 +6) 3/2 Math 8, Solutions to Review for the Final Exam Question : The distance is 5 t t + dt To work that out, integrate by parts with u t +, so that t dt du The integral is t t + dt u du u 3/ (t +) 3/ So the

More information

Partial Fractions. June 27, In this section, we will learn to integrate another class of functions: the rational functions.

Partial Fractions. June 27, In this section, we will learn to integrate another class of functions: the rational functions. Partial Fractions June 7, 04 In this section, we will learn to integrate another class of functions: the rational functions. Definition. A rational function is a fraction of two polynomials. For example,

More information

Math Lecture 4 Limit Laws

Math Lecture 4 Limit Laws Math 1060 Lecture 4 Limit Laws Outline Summary of last lecture Limit laws Motivation Limits of constants and the identity function Limits of sums and differences Limits of products Limits of polynomials

More information

Hölder s and Minkowski s Inequality

Hölder s and Minkowski s Inequality Hölder s and Minkowski s Inequality James K. Peterson Deartment of Biological Sciences and Deartment of Mathematical Sciences Clemson University Setember 10, 2018 Outline 1 Conjugate Exonents 2 Hölder

More information

Lecture 9: Taylor Series

Lecture 9: Taylor Series Math 8 Instructor: Padraic Bartlett Lecture 9: Taylor Series Week 9 Caltech 212 1 Taylor Polynomials and Series When we first introduced the idea of the derivative, one of the motivations we offered was

More information

Consequences of Continuity

Consequences of Continuity Consequences of Continuity James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University October 4, 2017 Outline 1 Domains of Continuous Functions 2 The

More information

Chapter 5: Integrals

Chapter 5: Integrals Chapter 5: Integrals Section 5.5 The Substitution Rule (u-substitution) Sec. 5.5: The Substitution Rule We know how to find the derivative of any combination of functions Sum rule Difference rule Constant

More information

Function Composition and Chain Rules

Function Composition and Chain Rules Function Composition and s James K. Peterson Department of Biological Sciences and Department of Matematical Sciences Clemson University Marc 8, 2017 Outline 1 Function Composition and Continuity 2 Function

More information

3.1 Derivative Formulas for Powers and Polynomials

3.1 Derivative Formulas for Powers and Polynomials 3.1 Derivative Formulas for Powers and Polynomials First, recall that a derivative is a function. We worked very hard in 2.2 to interpret the derivative of a function visually. We made the link, in Ex.

More information

MATH 250 TOPIC 13 INTEGRATION. 13B. Constant, Sum, and Difference Rules

MATH 250 TOPIC 13 INTEGRATION. 13B. Constant, Sum, and Difference Rules Math 5 Integration Topic 3 Page MATH 5 TOPIC 3 INTEGRATION 3A. Integration of Common Functions Practice Problems 3B. Constant, Sum, and Difference Rules Practice Problems 3C. Substitution Practice Problems

More information

Defining Exponential Functions and Exponential Derivatives and Integrals

Defining Exponential Functions and Exponential Derivatives and Integrals Defining Exponential Functions and Exponential Derivatives and Integrals James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University February 19, 2014

More information

Section 10.7 Taylor series

Section 10.7 Taylor series Section 10.7 Taylor series 1. Common Maclaurin series 2. s and approximations with Taylor polynomials 3. Multiplication and division of power series Math 126 Enhanced 10.7 Taylor Series The University

More information

MSM120 1M1 First year mathematics for civil engineers Revision notes 3

MSM120 1M1 First year mathematics for civil engineers Revision notes 3 MSM0 M First year mathematics for civil engineers Revision notes Professor Robert. Wilson utumn 00 Functions Definition of a function: it is a rule which, given a value of the independent variable (often

More information

Chapter 2 Derivatives

Chapter 2 Derivatives Contents Chapter 2 Derivatives Motivation to Chapter 2 2 1 Derivatives and Rates of Change 3 1.1 VIDEO - Definitions................................................... 3 1.2 VIDEO - Examples and Applications

More information

Lecture 4: Constructing the Integers, Rationals and Reals

Lecture 4: Constructing the Integers, Rationals and Reals Math/CS 20: Intro. to Math Professor: Padraic Bartlett Lecture 4: Constructing the Integers, Rationals and Reals Week 5 UCSB 204 The Integers Normally, using the natural numbers, you can easily define

More information

Section 5-7 : Green's Theorem

Section 5-7 : Green's Theorem Section 5-7 : Green's Theorem In this section we are going to investigate the relationship between certain kinds of line integrals (on closed paths) and double integrals. Let s start off with a simple

More information

How to write maths (well)

How to write maths (well) How to write maths (well) Dr Euan Spence 29 September 2017 These are the slides from a talk I gave to the new first-year students at Bath, annotated with some of the things I said (which appear in boxes

More information

Integrals. D. DeTurck. January 1, University of Pennsylvania. D. DeTurck Math A: Integrals 1 / 61

Integrals. D. DeTurck. January 1, University of Pennsylvania. D. DeTurck Math A: Integrals 1 / 61 Integrals D. DeTurck University of Pennsylvania January 1, 2018 D. DeTurck Math 104 002 2018A: Integrals 1 / 61 Integrals Start with dx this means a little bit of x or a little change in x If we add up

More information

Section 3.3 Product and Quotient rules 1 Lecture. Dr. Abdulla Eid. College of Science. MATHS 101: Calculus I

Section 3.3 Product and Quotient rules 1 Lecture. Dr. Abdulla Eid. College of Science. MATHS 101: Calculus I Section 3.3 Product and Quotient rules 1 Lecture College of Science MATHS 101: Calculus I (University of Bahrain) Differentiation Rules 1 / 12 Motivation Goal: We want to derive rules to find the derivative

More information

CMU CS 462/662 (INTRO TO COMPUTER GRAPHICS) HOMEWORK 0.0 MATH REVIEW/PREVIEW LINEAR ALGEBRA

CMU CS 462/662 (INTRO TO COMPUTER GRAPHICS) HOMEWORK 0.0 MATH REVIEW/PREVIEW LINEAR ALGEBRA CMU CS 462/662 (INTRO TO COMPUTER GRAPHICS) HOMEWORK 0.0 MATH REVIEW/PREVIEW LINEAR ALGEBRA Andrew ID: ljelenak August 25, 2018 This assignment reviews basic mathematical tools you will use throughout

More information

DIFFERENTIAL EQUATIONS

DIFFERENTIAL EQUATIONS DIFFERENTIAL EQUATIONS Basic Concepts Paul Dawkins Table of Contents Preface... Basic Concepts... 1 Introduction... 1 Definitions... Direction Fields... 8 Final Thoughts...19 007 Paul Dawkins i http://tutorial.math.lamar.edu/terms.aspx

More information

1 Limits and continuity

1 Limits and continuity 1 Limits and continuity Question 1. Which of the following its can be evaluated by continuity ( plugging in )? sin(x) (a) x + 1 (d) x 3 x 2 + x 6 (b) e x sin(x) (e) x 2 + x 6 (c) x 2 x 2 + x 6 (f) n (

More information

Fourier Sin and Cos Series and Least Squares Convergence

Fourier Sin and Cos Series and Least Squares Convergence Fourier Sin and Cos Series and east Squares Convergence James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University December 4, 208 Outline Sin and Cos

More information

MAT137 - Term 2, Week 2

MAT137 - Term 2, Week 2 MAT137 - Term 2, Week 2 This lecture will assume you have watched all of the videos on the definition of the integral (but will remind you about some things). Today we re talking about: More on the definition

More information

Generating Function Notes , Fall 2005, Prof. Peter Shor

Generating Function Notes , Fall 2005, Prof. Peter Shor Counting Change Generating Function Notes 80, Fall 00, Prof Peter Shor In this lecture, I m going to talk about generating functions We ve already seen an example of generating functions Recall when we

More information

Take the Anxiety Out of Word Problems

Take the Anxiety Out of Word Problems Take the Anxiety Out of Word Problems I find that students fear any problem that has words in it. This does not have to be the case. In this chapter, we will practice a strategy for approaching word problems

More information

Section Example Determine the Maclaurin series of f (x) = e x and its the interval of convergence.

Section Example Determine the Maclaurin series of f (x) = e x and its the interval of convergence. Example Determine the Maclaurin series of f (x) = e x and its the interval of convergence. Example Determine the Maclaurin series of f (x) = e x and its the interval of convergence. f n (0)x n Recall from

More information

Solving Quadratic & Higher Degree Equations

Solving Quadratic & Higher Degree Equations Chapter 7 Solving Quadratic & Higher Degree Equations Sec 1. Zero Product Property Back in the third grade students were taught when they multiplied a number by zero, the product would be zero. In algebra,

More information

MATH 1902: Mathematics for the Physical Sciences I

MATH 1902: Mathematics for the Physical Sciences I MATH 1902: Mathematics for the Physical Sciences I Dr Dana Mackey School of Mathematical Sciences Room A305 A Email: Dana.Mackey@dit.ie Dana Mackey (DIT) MATH 1902 1 / 46 Module content/assessment Functions

More information

f(x 0 + h) f(x 0 ) h slope of secant line = m sec

f(x 0 + h) f(x 0 ) h slope of secant line = m sec Derivatives Using limits, we can define the slope of a tangent line to a function. When given a function f(x), and given a point P (x 0, f(x 0 )) on f, if we want to find the slope of the tangent line

More information

First Derivative Test

First Derivative Test MA 2231 Lecture 22 - Concavity and Relative Extrema Wednesday, November 1, 2017 Objectives: Introduce the Second Derivative Test and its limitations. First Derivative Test When looking for relative extrema

More information

5.1 Simplifying Rational Expressions

5.1 Simplifying Rational Expressions 5. Simplifying Rational Expressions Now that we have mastered the process of factoring, in this chapter, we will have to use a great deal of the factoring concepts that we just learned. We begin with the

More information

Math 480 The Vector Space of Differentiable Functions

Math 480 The Vector Space of Differentiable Functions Math 480 The Vector Space of Differentiable Functions The vector space of differentiable functions. Let C (R) denote the set of all infinitely differentiable functions f : R R. Then C (R) is a vector space,

More information

Introduction to Series and Sequences Math 121 Calculus II Spring 2015

Introduction to Series and Sequences Math 121 Calculus II Spring 2015 Introduction to Series and Sequences Math Calculus II Spring 05 The goal. The main purpose of our study of series and sequences is to understand power series. A power series is like a polynomial of infinite

More information

Parametric Equations, Function Composition and the Chain Rule: A Worksheet

Parametric Equations, Function Composition and the Chain Rule: A Worksheet Parametric Equations, Function Composition and the Chain Rule: A Worksheet Prof.Rebecca Goldin Oct. 8, 003 1 Parametric Equations We have seen that the graph of a function f(x) of one variable consists

More information

Q You mentioned that in complex analysis we study analytic functions, or, in another name, holomorphic functions. Pray tell me, what are they?

Q You mentioned that in complex analysis we study analytic functions, or, in another name, holomorphic functions. Pray tell me, what are they? COMPLEX ANALYSIS PART 2: ANALYTIC FUNCTIONS Q You mentioned that in complex analysis we study analytic functions, or, in another name, holomorphic functions. Pray tell me, what are they? A There are many

More information

Main topics for the First Midterm

Main topics for the First Midterm Main topics for the First Midterm Midterm 2 will cover Sections 7.7-7.9, 8.1-8.5, 9.1-9.2, 11.1-11.2. This is roughly the material from the first five homeworks and and three quizzes. In particular, I

More information

Eigenvalues and Eigenvectors

Eigenvalues and Eigenvectors LECTURE 3 Eigenvalues and Eigenvectors Definition 3.. Let A be an n n matrix. The eigenvalue-eigenvector problem for A is the problem of finding numbers λ and vectors v R 3 such that Av = λv. If λ, v are

More information

2.5 The Chain Rule Brian E. Veitch

2.5 The Chain Rule Brian E. Veitch 2.5 The Chain Rule This is our last ifferentiation rule for this course. It s also one of the most use. The best way to memorize this (along with the other rules) is just by practicing until you can o

More information

Chapter 1 Functions and Limits

Chapter 1 Functions and Limits Contents Chapter 1 Functions and Limits Motivation to Chapter 1 2 4 Tangent and Velocity Problems 3 4.1 VIDEO - Secant Lines, Average Rate of Change, and Applications......................... 3 4.2 VIDEO

More information

Aim: How do we prepare for AP Problems on limits, continuity and differentiability? f (x)

Aim: How do we prepare for AP Problems on limits, continuity and differentiability? f (x) Name AP Calculus Date Supplemental Review 1 Aim: How do we prepare for AP Problems on limits, continuity and differentiability? Do Now: Use the graph of f(x) to evaluate each of the following: 1. lim x

More information

Complex Differentials and the Stokes, Goursat and Cauchy Theorems

Complex Differentials and the Stokes, Goursat and Cauchy Theorems Complex Differentials and the Stokes, Goursat and Cauchy Theorems Benjamin McKay June 21, 2001 1 Stokes theorem Theorem 1 (Stokes) f(x, y) dx + g(x, y) dy = U ( g y f ) dx dy x where U is a region of the

More information

Section 3.6 The chain rule 1 Lecture. Dr. Abdulla Eid. College of Science. MATHS 101: Calculus I

Section 3.6 The chain rule 1 Lecture. Dr. Abdulla Eid. College of Science. MATHS 101: Calculus I Section 3.6 The chain rule 1 Lecture College of Science MATHS 101: Calculus I (University of Bahrain) Logarithmic Differentiation 1 / 1 Motivation Goal: We want to derive rules to find the derivative of

More information

Calculating the Derivative Using Derivative Rules Implicit Functions Higher-Order Derivatives

Calculating the Derivative Using Derivative Rules Implicit Functions Higher-Order Derivatives Topic 4 Outline 1 Derivative Rules Calculating the Derivative Using Derivative Rules Implicit Functions Higher-Order Derivatives D. Kalajdzievska (University of Manitoba) Math 1500 Fall 2015 1 / 32 Topic

More information

Linear Systems of ODE: Nullclines, Eigenvector lines and trajectories

Linear Systems of ODE: Nullclines, Eigenvector lines and trajectories Linear Systems of ODE: Nullclines, Eigenvector lines and trajectories James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University October 6, 203 Outline

More information

Calculus & Analytic Geometry I

Calculus & Analytic Geometry I TQS 124 Autumn 2008 Quinn Calculus & Analytic Geometry I The Derivative: Analytic Viewpoint Derivative of a Constant Function. For c a constant, the derivative of f(x) = c equals f (x) = Derivative of

More information

Chapter P: Preliminaries

Chapter P: Preliminaries Chapter P: Preliminaries Spring 2018 Department of Mathematics Hong Kong Baptist University 1 / 67 Preliminaries The preliminary chapter reviews the most important things that you should know before beginning

More information

MAT137 - Term 2, Week 4

MAT137 - Term 2, Week 4 MAT137 - Term 2, Week 4 Reminders: Your Problem Set 6 is due tomorrow at 3pm. Test 3 is next Friday, February 3, at 4pm. See the course website for details. Today we will: Talk more about substitution.

More information

Differentiation. Timur Musin. October 10, University of Freiburg 1 / 54

Differentiation. Timur Musin. October 10, University of Freiburg 1 / 54 Timur Musin University of Freiburg October 10, 2014 1 / 54 1 Limit of a Function 2 2 / 54 Literature A. C. Chiang and K. Wainwright, Fundamental methods of mathematical economics, Irwin/McGraw-Hill, Boston,

More information

function independent dependent domain range graph of the function The Vertical Line Test

function independent dependent domain range graph of the function The Vertical Line Test Functions A quantity y is a function of another quantity x if there is some rule (an algebraic equation, a graph, a table, or as an English description) by which a unique value is assigned to y by a corresponding

More information

Computer Problems for Fourier Series and Transforms

Computer Problems for Fourier Series and Transforms Computer Problems for Fourier Series and Transforms 1. Square waves are frequently used in electronics and signal processing. An example is shown below. 1 π < x < 0 1 0 < x < π y(x) = 1 π < x < 2π... and

More information

Solving Quadratic & Higher Degree Equations

Solving Quadratic & Higher Degree Equations Chapter 9 Solving Quadratic & Higher Degree Equations Sec 1. Zero Product Property Back in the third grade students were taught when they multiplied a number by zero, the product would be zero. In algebra,

More information

MSM120 1M1 First year mathematics for civil engineers Revision notes 4

MSM120 1M1 First year mathematics for civil engineers Revision notes 4 MSM10 1M1 First year mathematics for civil engineers Revision notes 4 Professor Robert A. Wilson Autumn 001 Series A series is just an extended sum, where we may want to add up infinitely many numbers.

More information

Conceptual Explanations: Radicals

Conceptual Explanations: Radicals Conceptual Eplanations: Radicals The concept of a radical (or root) is a familiar one, and was reviewed in the conceptual eplanation of logarithms in the previous chapter. In this chapter, we are going

More information

One-Variable Calculus

One-Variable Calculus POLI 270 - Mathematical and Statistical Foundations Department of Political Science University California, San Diego September 30, 2010 1 s,, 2 al Relationships Political Science, economics, sociology,

More information

Math 229 Mock Final Exam Solution

Math 229 Mock Final Exam Solution Name: Math 229 Mock Final Exam Solution Disclaimer: This mock exam is for practice purposes only. No graphing calulators TI-89 is allowed on this test. Be sure that all of your work is shown and that it

More information

Chapter 12: Differentiation. SSMth2: Basic Calculus Science and Technology, Engineering and Mathematics (STEM) Strands Mr. Migo M.

Chapter 12: Differentiation. SSMth2: Basic Calculus Science and Technology, Engineering and Mathematics (STEM) Strands Mr. Migo M. Chapter 12: Differentiation SSMth2: Basic Calculus Science and Technology, Engineering and Mathematics (STEM) Strands Mr. Migo M. Mendoza Chapter 12: Differentiation Lecture 12.1: The Derivative Lecture

More information

MATH 408N PRACTICE FINAL

MATH 408N PRACTICE FINAL 2/03/20 Bormashenko MATH 408N PRACTICE FINAL Show your work for all the problems. Good luck! () Let f(x) = ex e x. (a) [5 pts] State the domain and range of f(x). Name: TA session: Since e x is defined

More information

1. Use the properties of exponents to simplify the following expression, writing your answer with only positive exponents.

1. Use the properties of exponents to simplify the following expression, writing your answer with only positive exponents. Math120 - Precalculus. Final Review. Fall, 2011 Prepared by Dr. P. Babaali 1 Algebra 1. Use the properties of exponents to simplify the following expression, writing your answer with only positive exponents.

More information

Linear Systems of ODE: Nullclines, Eigenvector lines and trajectories

Linear Systems of ODE: Nullclines, Eigenvector lines and trajectories Linear Systems of ODE: Nullclines, Eigenvector lines and trajectories James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University October 6, 2013 Outline

More information

1.10 Continuity Brian E. Veitch

1.10 Continuity Brian E. Veitch 1.10 Continuity Definition 1.5. A function is continuous at x = a if 1. f(a) exists 2. lim x a f(x) exists 3. lim x a f(x) = f(a) If any of these conditions fail, f is discontinuous. Note: From algebra

More information

LIMITS AND DERIVATIVES

LIMITS AND DERIVATIVES 2 LIMITS AND DERIVATIVES LIMITS AND DERIVATIVES 2.2 The Limit of a Function In this section, we will learn: About limits in general and about numerical and graphical methods for computing them. THE LIMIT

More information

This format is the result of tinkering with a mixed lecture format for 3 terms. As such, it is still a work in progress and we will discuss

This format is the result of tinkering with a mixed lecture format for 3 terms. As such, it is still a work in progress and we will discuss Version 1, August 2016 1 This format is the result of tinkering with a mixed lecture format for 3 terms. As such, it is still a work in progress and we will discuss adaptations both to the general format

More information

Review of Power Series

Review of Power Series Review of Power Series MATH 365 Ordinary Differential Equations J. Robert Buchanan Department of Mathematics Fall 2018 Introduction In addition to the techniques we have studied so far, we may use power

More information