d dx [xn ] = nx n 1. (1) dy dx = 4x4 1 = 4x 3. Theorem 1.3 (Derivative of a constant function). If f(x) = k and k is a constant, then f (x) = 0.

Similar documents
Differentiation Rules Derivatives of Polynomials and Exponential Functions

Lecture 4 : General Logarithms and Exponentials. a x = e x ln a, a > 0.

f(x) f(a) Limit definition of the at a point in slope notation.

1 Definition of the derivative

JUST THE MATHS UNIT NUMBER DIFFERENTIATION 2 (Rates of change) A.J.Hobson

Final Exam Study Guide and Practice Problems Solutions

Math 115 Section 018 Course Note

Math Chapter 2 Essentials of Calculus by James Stewart Prepared by Jason Gaddis

1 Lecture 13: The derivative as a function.

By writing (1) as y (x 5 1). (x 5 1), we can find the derivative using the Product Rule: y (x 5 1) 2. we know this from (2)

You should also review L Hôpital s Rule, section 3.6; follow the homework link above for exercises.

Differentiation ( , 9.5)

February 21 Math 1190 sec. 63 Spring 2017

QF101: Quantitative Finance September 5, Week 3: Derivatives. Facilitator: Christopher Ting AY 2017/2018. f ( x + ) f(x) f(x) = lim

1 Limits Finding limits graphically. 1.3 Finding limits analytically. Examples 1. f(x) = x3 1. f(x) = f(x) =

Math 251 Notes. Part I.

SYDE 112, LECTURE 1: Review & Antidifferentiation

The derivative of a function f(x) is another function, defined in terms of a limiting expression: f(x + δx) f(x)

Calculus I Announcements

Math 190 Chapter 3 Lecture Notes. Professor Miguel Ornelas

Chapter 1. Functions, Graphs, and Limits

Derivatives. if such a limit exists. In this case when such a limit exists, we say that the function f is differentiable.

Differentiation Rules and Formulas

DERIVATIVES: LAWS OF DIFFERENTIATION MR. VELAZQUEZ AP CALCULUS

1 Lecture 18: The chain rule

Review of Differentiation and Integration for Ordinary Differential Equations

Chapter 3 Notes, Applied Calculus, Tan

Lectures - Week 10 Introduction to Ordinary Differential Equations (ODES) First Order Linear ODEs

Chapter 2. Exponential and Log functions. Contents

MATH 120 Theorem List

Chapter 3 Definitions and Theorems

0.1 The Chain Rule. db dt = db

MATH 1300 Lecture Notes Wednesday, September 25, 2013

THEOREM: THE CONSTANT RULE

Differentiability, Computing Derivatives, Trig Review. Goals:

Define each term or concept.

Outline. MS121: IT Mathematics. Differentiation Rules for Differentiation: Part 1. Outline. Dublin City University 4 The Quotient Rule

MAT01A1: Differentiation of Polynomials & Exponential Functions + the Product & Quotient Rules

Differentiability, Computing Derivatives, Trig Review

x 2 2x 8 (x 4)(x + 2)

Implicit Differentiation and Inverse Trigonometric Functions

1 Lecture 20: Implicit differentiation

MA123, Supplement: Exponential and logarithmic functions (pp , Gootman)

Derivatives of Constant and Linear Functions

Section The Chain Rule and Implicit Differentiation with Application on Derivative of Logarithm Functions

Math 180, Exam 2, Fall 2012 Problem 1 Solution. (a) The derivative is computed using the Chain Rule twice. 1 2 x x

Linear and quadratic approximation

P(x) = 1 + x n. (20.11) n n φ n(x) = exp(x) = lim φ (x) (20.8) Our first task for the chain rule is to find the derivative of the exponential

Section 3.1/3.2: Rules of Differentiation

Math 210 Midterm #1 Review

Some functions and their derivatives

Chapter 7. Integrals and Transcendental Functions

( 3x +1) 2 does not fit the requirement of the power rule that the base be x

Quantum Mechanics in Three Dimensions

Math 106 Exam 2 Topics. du dx

016A Homework 10 Solution

Implicit Differentiation

2.4 Exponential Functions and Derivatives (Sct of text)

x = c of N if the limit of f (x) = L and the right-handed limit lim f ( x)

Fall 2016: Calculus I Final

cosh x sinh x So writing t = tan(x/2) we have 6.4 Integration using tan(x/2) = 2 2t 1 + t 2 cos x = 1 t2 We will revisit the double angle identities:

Chapter 2. First-Order Differential Equations

First Order Linear Differential Equations

Calculus and optimization

1. Find the equation of a line passing through point (5, -2) with slope ¾. (State your answer in slope-int. form)

MA Midterm Exam 1 Spring 2012

Calculus I Practice Test Problems for Chapter 3 Page 1 of 9

Math 2163, Practice Exam II, Solution

Flash Card Construction Instructions

Summary: Differentiation

Table of Contents Derivatives of Logarithms

Implicit Differentiation. Lecture 16.

Mathematical Review Problems

Hyperbolic Functions. Notice: this material must not be used as a substitute for attending. the lectures

Make graph of g by adding c to the y-values. on the graph of f by c. multiplying the y-values. even-degree polynomial. graph goes up on both sides

Solutions to Math 41 Second Exam November 4, 2010

Your signature: (1) (Pre-calculus Review Set Problems 80 and 124.)

ARAB ACADEMY FOR SCIENCE TECHNOLOGY AND MARITIME TRANSPORT

23 Implicit differentiation

CHAPTER 1 : DIFFERENTIABLE MANIFOLDS. 1.1 The definition of a differentiable manifold

2.1 Derivatives and Rates of Change

Section 7.1: Integration by Parts

MAT1A01: Differentiation of Polynomials & Exponential Functions + the Product & Quotient Rules

Lagrangian and Hamiltonian Mechanics

Optimization Notes. Note: Any material in red you will need to have memorized verbatim (more or less) for tests, quizzes, and the final exam.

Section 7.2. The Calculus of Complex Functions

cosh x sinh x So writing t = tan(x/2) we have 6.4 Integration using tan(x/2) 2t 1 + t 2 cos x = 1 t2 sin x =

Implicit Differentiation

Math Review for Physical Chemistry

11.7. Implicit Differentiation. Introduction. Prerequisites. Learning Outcomes

IMPLICIT DIFFERENTIATION

7.1. Calculus of inverse functions. Text Section 7.1 Exercise:

Derivatives and the Product Rule

AP Calculus AB One Last Mega Review Packet of Stuff. Take the derivative of the following. 1.) 3.) 5.) 7.) Determine the limit of the following.

Math 1271 Solutions for Fall 2005 Final Exam

Applications of the Wronskian to ordinary linear differential equations

CHAPTER 3 DERIVATIVES (continued)

Exam 3 Review. Lesson 19: Concavity, Inflection Points, and the Second Derivative Test. Lesson 20: Absolute Extrema on an Interval

Derivatives and Its Application

Chapter 2 Derivatives

Transcription:

Calculus refresher Disclaimer: I claim no original content on this ocument, which is mostly a summary-rewrite of what any stanar college calculus book offers. (Here I ve use Calculus by Dennis Zill.) I consier this as a brief refresher of the bare-bones calculus requirements we will be using uring the course. No exercises are offere: any calculus book provies an insane amount of practice problems. 1. Rules of ifferentiation: Basics In what follows, let f(x) be a one-variable function, an enote its erivative by f (x). ifferentiation rules are the following: Theorem 1.1 (The Power Rule, 1). Let n be a positive integer. Then The stanar Example 1.2. The erivative of y = x 4 is given by x [xn ] = nx n 1. (1) x = 4x4 1 = 4x 3. Theorem 1.3 (Derivative of a constant function). If f(x) = k an k is a constant, then f (x) = 0. Theorem 1.4 (Derivative of a constant multiple of a function). If c is any constant an f is a ifferentiable function, then x [cf(x)] = cf (x). (2) Example 1.5. Following theorems 1.1 an 1.4, the erivative of y = 3x 5 is given by: x = 3 x x5 = 3(5x 4 ) = 15x 4. Theorem 1.6 (The Sum Rule). Let f an g be two ifferentiable functions. Then x [f(x) + g(x)] = f (x) + g (x). (3) Example 1.7. From theorems 1.1. an 1.6, the erivative of y = x 4 + x 3 is: x = x x4 + x x3 = 4x 3 + 3x 2. Theorem 1.8 (The Prouct Rule). If f an g are ifferentiable functions, then Example 1.9. The ifferential of y = (x 3 2x 2 + 4)(8x 2 + 5x) is: x [f(x)g(x)] = f(x)g (x) + g(x)f (x). (4) x = (x3 2x 2 + 4) x (8x2 + 5x) + (8x 2 + 5x) x (x3 2x 2 + 4) = (x 3 2x 2 + 4)(16x + 5) + (8x 2 + 5x)(3x 2 4x). Theorem 1.10 (The Quotient Rule). If f an g are ifferentiable functions, then [ ] f(x) x g(x) = g(x)f (x) f(x)g (x) [g(x)] 2. (5) 1

2 Example 1.11. The ifferential of y = 3x2 1 2x 3 +5x 2 +7 is: x = (2x3 + 5x 2 + 7) x (3x2 1) (3x 2 1) x (2x3 + 5x 2 + 7) (2x 3 + 5x 2 + 7) 2 = (2x3 + 5x 2 + 7) (6x) (3x 2 1) (6x 2 + 10x) (2x 3 + 5x 2 + 7) 2 = 6x4 + 6x 2 + 52x (2x 3 + 5x 2 + 7) 2. Theorem 1.12 (The Power Rule, 2). If n is a positive integer, then x [x n ] = nx n 1. (6) Example 1.13. The erivative of y = 5x 3 1 x 4 is (after rewriting y as 5x 3 x 4 ): x = 5 3x2 ( 4)x 5 = 15x 2 + 4 x 5. 2. Rules of ifferentiation: The Chain Rule Theorem 2.1 (The Power Rule for Functions). If n is an integer an g is a ifferentiable function, then x [g(x)]n = n[g(x)] n 1 g (x). (7) Example 2.2. Let y = (2x 3 + 4x + 1) 4. If g(x) = (2x 3 + 4x + 1) an n = 4, then from Theorem 2.1 it follows that x = 4(2x3 + 4x + 1) 3 x (2x3 + 4x + 1) = 4(2x 3 + 4x + 1) 3 (6x 2 + 4). Theorem 2.3 (The Chain Rule). If y = f(u) is a ifferentiable function of u an u = g(x) is a ifferentiable function of x, then x = u u x = f (g(x)) g (x). (8) Example 2.4. From the rules of ifferentiation of trigonometric functions, it is true that: [sin u] = cos uu x x. Let y = (9x 3 + 1) 2 sin 5x. Then, the erivative of y can be obtaine first by applying Theorem 1.8: followe by applications of theorems 2.1 an 2.2: x = (9x3 + 1) 2 sin 5x + sin 5x x x (9x3 + 1) 2, x = (9x3 + 1) 2 5 cos 5x + sin 5x 2(9x 3 + 1) (27x 2 ) = (9x 3 + 1)(45x 3 cos 5x + 54x 2 sin 5x + 5 cos 5x).

3 3. Higher-orer erivatives Definition 3.1 (The Secon Derivative). The erivative f (x) is a function erive from a function y = f(x). By ifferentiating the first erivative f (x), we obtain yet another function calle the secon erivative, enote by f (x). In terms of the operation symbol x ( x : ). x Alternative notation for the secon erivative is given by: f (x), y, 2 y x 2, an D 2 xy. Example 3.2. To calculate the secon erivative of y = x 3 2x 2, first we obtain x : Then, the secon erivative is: x = 3x2 4x. 2 y x 2 = x (3x2 4x) = 6x 4. Remark 3.3. Higher-orer erivatives are obtaine analogously: the thir erivative is the erivative of the secon erivative; the fourth erivative is the erivative of the thir erivative, an so on. A stanar notation for the first n erivatives is (among others) f (x), f (x), f (x), f (4) (x),..., f (n) (x). Example 3.4. The first five erivatives of the polynomial f(x) = 2x 4 6x 3 + 7x 2 + 5x 10 are given by: f (x) = 8x 3 18x 2 + 14x + 5, f (x) = 24x 2 36x + 14, f (x) = 48x 36, f (4) (x) = 48, f (5) (x) = 0. 4. Extremals of functions Definition 4.1 (Absolute extremals). Let f be a real-value function. The absolute extremals of f are efine as follows: (a) A number f( c) is an absolute maximum if f(x) f( c) for every x in the omain of f. (b) A number f( c) is an absolute minimum if f(x) f( c) for every x in the omain of f. Theorem 4.2 (The Extreme Value Theorem). A continuous function f efine on a close interval [a, b] always has an absolute maximum an an absolute minimum on the interval. Definition 4.3 (Critical point). A critical point of a function f is a number c in its omain for which f (c) = 0. Example 4.4. To fin the critical points of f(x) = x 3 15x + 6, we obtain the first erivative f (x): f (x) = 3x 2 15 = 3(x + 5)(x 5). Hence, the critical points are those numbers for which f (x) = 0, namely, 5 an 5. Theorem 4.5. If f is continuous on a close interval [a, b], then an absolute extremum occurs either at an enpoint of the interval or at a critical point in the open interval (a, b). Remark 4.6. The previous theorem says that any absolute extremum must occur in an enpoint or in a critical point. This is not the same as assuming that because we have a critical point, it must be an extremum! Secon-orer conitions shoul be checke to verify that we have a minimum or maximum.

4 Example 4.7. Let f(x) = x 3 3x 2 24x + 2 be efine on the intervals [ 3, 1] an [ 3, 8]. To fin the absolute extremals, first we obtain f (x): f (x) = 3x 2 6x 24 = 3(x + 2)(x 4), an it follows that the critical points of the function are -2 an 4. Simple calculations show that for the interval [ 3, 1], the absolute maximum is f( 2) = 30, an the absolute minimum is the enpoint extremum f(1) = 24. For the interval [ 3, 8], the absolute minimum is f(4) = 78, while the absolute maximum is reache at the enpoint extremum f(8) = 130. 5. The natural logarithmic function Definition 5.1 (The Natural Logarithmic Function). The natural logarithmic function, enote by ln x, 1 is efine by: for all x > 0. ln x = Theorem 5.2 (The Derivative of the Natural Logarithm). The erivative of ln x is given by: x 1 t t (9) for all x > 0. x [ln x] = 1 x, (10) Theorem 5.3 (Laws of the Natural Logarithm). Let a an b be positive real numbers an let t be a rational number. Then: (a) ln ab = ln a + ln b. (b) ln a b = ln a ln b. (c) ln a t = t ln a. Example 5.4. To obtain the erivative of y = ln(2x 3), note that for 2x 3 > 0, we have from Theorem 7.2: x = 1 2x 3 x (2x 3) = 2 2x 3. 6. The exponential function Definition 6.1 (The Natural Exponential Function). The natural exponential function is efine by: For any real number x, e x = exp x. y = exp x if an only if x = ln y. (11) Theorem 6.2 (Laws of Exponents). Let r an s be any real numbers an let t be a rational number. Then: (a) e 0 = 1. (b) e 1 = e. (c) e r e s = e r+s. () er e = e r s. s (e) (e r ) t = e rt. (f) e r = 1 e. r 1 Usually the symbol ln x is pronounce ell-en of x

5 Theorem 6.3 (The erivative of the exponential function). The erivative of y = exp x is given by: Using the Chain Rule, we can generalize the above to where u = g(x) is a ifferentiable function. Example 6.4. The erivative of y = e 4x is given by: x [ex ] = e x. (12) x [eu ] = e u u x, (13) x = e4x x (4x) = e 4x (4) = 4e 4x 7. Partial ifferentiation Remark 7.1 (Partial ifferentiation). Let z = f(x, y). To compute z/ x, use the laws of orinary ifferentiation while treating y as a constant. To compute z/ y, use the laws of orinary ifferentiation while treating x as a constant. Remark 7.2. If z = f(x, y), alternative notation for partial erivatives is z/ x = f/ x = z x = f x, an similarly, z/ y = f/ y = z y = f y. Example 7.3. Let z = 4x 3 y 2 4x 2 + y 6 + 1. The partial erivatives of z with respect to x an y are given by: z x = 12x2 y 2 8x z y = 8x 3 y + 6y 5. Theorem 7.4 (Equality of Mixe Partials). Let f be a function of two variables. If f x, f y, f xy, an f yx are continuous on an open region R, then f xy = f yx at each point of R. Example 7.5. Consier the partial erivatives obtaine in Example 7.3. The continuity conitions of Theorem 7.4 are satisfie in this case, so it shoul be that f xy = f yx ; this is so since 2 z x y = 24x 2 y 2 z y x = 24x2 y.