Functions of Several Variables

Slides:



Advertisements
Similar presentations
Chapter 17 Multivariable Calculus.
Advertisements

§ 7.2 Partial Derivatives.
Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Lagrange Multipliers OBJECTIVES  Find maximum and minimum values using Lagrange.
Slide Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley.
Copyright © 2008 Pearson Education, Inc. Chapter 9 Multivariable Calculus Copyright © 2008 Pearson Education, Inc.
Copyright © 2005 Pearson Education, Inc. Publishing as Pearson Addison-Wesley.
© 2010 Pearson Education, Inc. All rights reserved.
Copyright © 2011 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 4 Applications of the Derivative.
© 2010 Pearson Education Inc.Goldstein/Schneider/Lay/Asmar, CALCULUS AND ITS APPLICATIONS, 12e– Slide 1 of 62 Chapter 7 Functions of Several Variables.
© 2010 Pearson Education Inc.Goldstein/Schneider/Lay/Asmar, CALCULUS AND ITS APPLICATIONS, 12e– Slide 1 of 55 Chapter 4 The Exponential and Natural Logarithm.
Chapter 12 Additional Differentiation Topics.
Derivatives of Logarithmic Functions
5.4 Exponential Functions: Differentiation and Integration The inverse of f(x) = ln x is f -1 = e x. Therefore, ln (e x ) = x and e ln x = x Solve for.
Copyright © 2011 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 12 Functions of Several Variables.
Chapter 5 Section 1 Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley.
© 2010 Pearson Education Inc.Goldstein/Schneider/Lay/Asmar, CALCULUS AND ITS APPLICATIONS, 12e– Slide 1 of 33 Chapter 3 Techniques of Differentiation.
Section 5.3 – The Definite Integral
In this section, we will learn about: Differentiating composite functions using the Chain Rule. DIFFERENTIATION RULES 3.4 The Chain Rule.
Chapter 14 – Partial Derivatives 14.3 Partial Derivatives 1 Objectives:  Understand the various aspects of partial derivatives Dr. Erickson.
Copyright © Cengage Learning. All rights reserved. 4 Integrals.
4.1 The Indefinite Integral. Antiderivative An antiderivative of a function f is a function F such that Ex.An antiderivative of since is.
Section 3.3 The Product and Quotient Rule. Consider the function –What is its derivative? –What if we rewrite it as a product –Now what is the derivative?
Copyright © 2011 Pearson Education, Inc. Integral Exponents and Scientific Notation Section P.2 Prerequisites.
Copyright © 2015, 2008, 2011 Pearson Education, Inc. Section 4.1, Slide 1 Chapter 4 Exponential Functions.
Definition Section 4.1: Indefinite Integrals. The process of finding the indefinite integral of f(x) is called integration of f(x) or integrating f(x).
Properties of Logarithms log b (MN)= log b M + log b N Ex: log 4 (15)= log log 4 3 log b (M/N)= log b M – log b N Ex: log 3 (50/2)= log 3 50 – log.
© 2010 Pearson Education Inc.Goldstein/Schneider/Lay/Asmar, CALCULUS AND ITS APPLICATIONS, 12e– Slide 1 of 33 Chapter 3 Techniques of Differentiation.
2-1 The Derivative and the Tangent Line Problem 2-2 Basic Differentiation Rules and Rates of Change 2-3 Product/Quotient Rule and Higher-Order Derivatives.
Calculating the Derivative
§ 4.2 The Exponential Function e x.
Section 14.2 Computing Partial Derivatives Algebraically
Differential Equations
7 INVERSE FUNCTIONS.
Differential Equations
Copyright © Cengage Learning. All rights reserved.
Antiderivatives 5.1.
Functions of Several Variables
§ 1.3 The Derivative.
Section 3.7 Implicit Functions
Chapter 3 Techniques of Differentiation
DIFFERENTIATION RULES
CHAPTER 4 DIFFERENTIATION.
Techniques of Integration
Copyright (c) 2003 Brooks/Cole, a division of Thomson Learning, Inc.
Chapter 17 Multivariable Calculus.
§ 4.4 The Natural Logarithm Function.
Techniques for Finding Derivatives
Section 4.3 – Area and Definite Integrals
Applications of the Derivative
Copyright © 2014, 2010, 2007 Pearson Education, Inc.
Calculus (Make sure you study RS and WS 5.3)
Numerical Analysis Lecture 26.
PRELIMINARY MATHEMATICS
Derivatives and Graphs
Chapter 3 Section 6.
The Chain Rule Find the composition of two functions.
Differential Equations
§ 4.3 Differentiation of Exponential Functions.
Copyright © Cengage Learning. All rights reserved.
The Fundamental Theorem of Calculus
Chapter 6 The Definite Integral
Copyright © Cengage Learning. All rights reserved.
Chapter 7 Functions of Several Variables
Tutorial 4 Techniques of Differentiation
Techniques of Integration
Differentiation Techniques: The Power and Sum-Difference Rules
Section 5.3 – The Definite Integral
Section 5.3 – The Definite Integral
Chapter 3 Techniques of Differentiation
Exponential Functions Logarithmic Functions
Presentation transcript:

Functions of Several Variables Chapter 7 Functions of Several Variables Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Chapter Outline Examples of Functions of Several Variables Partial Derivatives Maxima and Minima of Functions of Several Variables Lagrange Multipliers and Constrained Optimization The Method of Least Squares Double Integrals Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Section 7.2 Partial Derivatives Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Section Outline Partial Derivatives Computing Partial Derivatives Evaluating Partial Derivatives at a Point Local Approximation of f (x, y) Demand Equations Second Partial Derivative Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Partial Derivatives If , then Partial Derivative of f (x, y) with respect to x: written , is the derivative of f (x, y), where y is treated as a constant and f (x, y) is considered as a function of x alone. The partial derivative of f(x, y) with respect to y, written , is the derivative of f(x,y), where x is treated as a constant. Example Definition Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Interpret Partial Derivatives as Slopes Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Computing Partial Derivatives EXAMPLE Compute for SOLUTION To compute , we only differentiate factors (or terms) that contain x and we interpret y to be a constant. This is the given function. Use the product rule where f (x) = x2 and g(x) = e3x. To compute , we only differentiate factors (or terms) that contain y and we interpret x to be a constant. Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Computing Partial Derivatives CONTINUED This is the given function. Differentiate ln y. Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Computing Partial Derivatives EXAMPLE Compute for SOLUTION To compute , we treat every variable other than L as a constant. Therefore This is the given function. Rewrite as an exponent. Bring exponent inside parentheses. Note that K is a constant. Differentiate. Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Evaluating Partial Derivatives at a Point EXAMPLE Let Evaluate at (x, y, z) = (2, -1, 3). SOLUTION Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Local Approximation of f (x, y) We can generalize the interpretations of to yield the following general fact: Partial derivatives can be computed for functions of any number of variables. When taking the partial derivative with respect to one variable, we treat the other variables as constant. Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Local Approximation of f (x, y) EXAMPLE Let Interpret the result SOLUTION We showed in the last example that This means that if x and z are kept constant and y is allowed to vary near -1, then f (x, y, z) changes at a rate 12 times the change in y (but in a negative direction). That is, if y increases by one small unit, then f (x, y, z) decreases by approximately 12 units. If y increases by h units (where h is small), then f (x, y, z) decreases by approximately 12h. That is, Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Demand Equations EXAMPLE The demand for a certain gas-guzzling car is given by f (p1, p2), where p1 is the price of the car and p2 is the price of gasoline. Explain why SOLUTION is the rate at which demand for the car changes as the price of the car changes. This partial derivative is always less than zero since, as the price of the car increases, the demand for the car will decrease (and visa versa). is the rate at which demand for the car changes as the price of gasoline changes. This partial derivative is always less than zero since, as the price of gasoline increases, the demand for the car will decrease (and visa versa). Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Higher Order Partial Derivatives Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Second Partial Derivative EXAMPLE Let . Find SOLUTION We first note that This means that to compute , we must take the partial derivative of with respect to x. Copyright © 2014, 2010, 2007 Pearson Education, Inc.

Copyright © 2014, 2010, 2007 Pearson Education, Inc. Incorporating Technology Example 4 Copyright © 2014, 2010, 2007 Pearson Education, Inc.